Medical Practice Management

Pulseboard

Command Your Clinic in Real Time

Pulseboard delivers real-time, unified clinic management for small practice managers by merging scheduling, billing, and patient flow into one intuitive dashboard. Live integrations spotlight bottlenecks and prevent costly errors, empowering managers to cut admin tasks, resolve issues instantly, and redirect focus from paperwork to patient care—restoring calm and control to every shift.

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Pulseboard

Product Details

Explore this AI-generated product idea in detail. Each aspect has been thoughtfully created to inspire your next venture.

Vision & Mission

Vision
To empower every small clinic to deliver seamless care by making real-time operational clarity and efficiency universally accessible.
Long Term Goal
By 2028, empower 25,000 small clinics to cut admin workload by 30% and improve patient throughput by 20%, elevating care efficiency for 10 million patients globally.
Impact
Reduces clinic administrative workload by 30% and billing errors by 15%, enabling small clinic managers to process patients 20% faster and reallocate over six hours per week from paperwork to patient care, directly improving operational control and reducing staff burnout.

Problem & Solution

Problem Statement
Small clinic managers juggle fragmented scheduling, billing, and patient flow tools, resulting in operational blind spots, revenue loss, and delays. Existing enterprise solutions are costly or complex, leaving small practices without accessible, real-time control over daily operations.
Solution Overview
Pulseboard unifies clinic scheduling, billing, and patient flow from multiple systems into a single, real-time dashboard, giving managers instant visibility. Live vendor integration and automated alerts eliminate manual data checks and highlight bottlenecks before they disrupt operations, reducing admin workload and costly errors.

Details & Audience

Description
Pulseboard is a real-time dashboard for small clinic managers that unifies scheduling, billing, and patient flow in one intuitive view. Practice managers gain instant visibility and control, swiftly spotting bottlenecks and preventing costly errors. Its standout feature is live integration with multiple vendors, eliminating manual data checks and freeing staff to focus on patients—not paperwork.
Target Audience
Clinic managers (30-55) at small medical practices seeking unified operations and rapid problem resolution.
Inspiration
Late one afternoon in a small clinic’s waiting room, I watched a manager juggle three screens and messy paper notes, frantically updating schedules while fielding impatient calls about billing. Each delay chipped away at patients’ trust and staff morale. In that moment, the need for a single, real-time dashboard—Pulseboard—became glaringly obvious: streamline the chaos, empower managers, and restore reassuring calm to care.

User Personas

Detailed profiles of the target users who would benefit most from this product.

S

Scaling Stella

- Age 38, MBA in healthcare management - Manages 3 clinic locations, 15+ staff - Oversees $2M annual revenue - 6 years in practice operations

Background

Started as a receptionist in a busy family practice, quickly promoted to office manager. After leading a second clinic opening, she learned the pain of disjointed systems during rapid growth.

Needs & Pain Points

Needs

1. Automated multi-site scheduling coordination 2. Unified reporting across all clinics 3. Real-time capacity and staffing alerts

Pain Points

1. Manual data consolidation across locations 2. Scheduling conflicts causing patient delays 3. Billing discrepancies due to system mismatch

Psychographics

- Seeks scalable, systemized workflows - Driven by strategic growth targets - Prefers data-backed operational decisions

Channels

1. Microsoft Teams (daily collaboration) 2. LinkedIn Pulse (industry updates) 3. Podcast – Healthcare Growth (weekly) 4. Email newsletters (management tips) 5. YouTube tutorials (system demos)

C

Compliance Clara

- Age 45, Masters in health administration - Certified medical auditor with 10 years’ experience - Manages compliance for 5 outpatient practices - Oversees quarterly regulatory audits

Background

Former medical auditor at a large hospital, Clara witnessed costly compliance breaches. Now specializing in outpatient clinics, she’s driven to close regulatory gaps before they become fines.

Needs & Pain Points

Needs

1. Detailed audit logs for every transaction 2. Automated HIPAA compliance reporting 3. Instant alerts on unauthorized data access

Pain Points

1. Hidden system access loops causing audit failures 2. Manual compliance report generation wasting hours 3. Unclear user permission hierarchies compromising security

Psychographics

- Zero tolerance for data security lapses - Motivated by regulatory risk mitigation - Values meticulous documentation and traceability

Channels

1. Compliance forums (monthly discussions) 2. Email alerts (critical updates) 3. LinkedIn Groups (regulation changes) 4. Government health sites (official guidelines) 5. Webinars (regulatory training)

T

Telehealth Ted

- Age 32, Bachelor’s in health informatics - Manages telehealth for 3 clinicians - Generates $500K annual telemedicine revenue - 4 years in telehealth coordination

Background

Shifted from IT support to telemedicine pioneer after COVID surges. He built virtual workflows from scratch, battling fragmented platforms and connectivity issues.

Needs & Pain Points

Needs

1. Native video integration within scheduling 2. Real-time virtual waiting room status 3. Automated teleconsultation follow-up reminders

Pain Points

1. Choppy video disrupting consultations 2. Double-booking from separate telehealth systems 3. Patients missing virtual room URLs

Psychographics

- Passionate about expanding remote access - Seeks frictionless digital patient interactions - Values interoperability of telehealth tools

Channels

1. Zoom (primary video) 2. Clinic portal (patient links) 3. Slack (team coordination) 4. Email (appointment confirmations) 5. App notifications (reminders)

O

Onboard Olivia

- Age 29, Degree in instructional design - Certified LMS administrator - Trains 20+ staff members - 3 years designing clinical training

Background

Started as a clinic receptionist, then informally trained new hires. She developed formal training programs for EMR rollouts and overcame widespread technical confusion.

Needs & Pain Points

Needs

1. Intuitive in-app training modules 2. Progress tracking for each user 3. Contextual tooltips and walkthroughs

Pain Points

1. Staff frustrated by complex interfaces 2. No real-time training feedback metrics 3. Outdated training materials post-update

Psychographics

- Dedicated to clear, engaging instruction - Empathetic towards tech-averse learners - Motivated by measurable training success

Channels

1. LMS portal (training modules) 2. Email (session updates) 3. In-app messages (guidance) 4. Zoom (live webinars) 5. Slack channel (Q&A)

H

Hybrid Henry

- Age 40, Oversees 2 clinics and telehealth - Manages $1M annual operations budget - 8 years in practice operations - Holds a healthcare management certificate

Background

After adding home-visit services, Henry struggled with separate scheduling systems. He now prioritizes tools merging physical and virtual calendars in real time.

Needs & Pain Points

Needs

1. Consolidated physical and virtual schedule view 2. Real-time location-based flow alerts 3. Instant mode-switch between care settings

Pain Points

1. Staff confusion when switching systems 2. Overlapping bookings across care modes 3. Manual location update drags workflows

Psychographics

- Values flexible, hybrid care models - Seeks balance between in-person and remote - Driven by staff work-life harmony

Channels

1. Google Calendar sync (daily overview) 2. Mobile app (on-the-go updates) 3. SMS alerts (schedule changes) 4. Microsoft Teams (team coordination) 5. Clinic dashboard (in-office use)

Product Features

Key capabilities that make this product valuable to its target users.

Threshold Tuner

Allows managers to set custom wait-time thresholds for different departments and appointment types, ensuring alerts align with unique clinic workflows and patient expectations.

Requirements

Threshold Configuration Interface
"As a small practice manager, I want an intuitive interface to define and adjust wait-time thresholds so that I can quickly tailor alert settings without technical assistance."
Description

The system shall present a user-friendly interface within Pulseboard's dashboard where authorized managers can create, edit, and save custom wait-time thresholds. The interface must include intuitive controls such as numeric input fields, slider bars, and preset template options. It integrates seamlessly with existing clinic settings, ensuring threshold changes are immediately available across modules. This requirement enhances usability by providing clear feedback on configured values, preventing configuration errors through inline validation, and supporting efficient threshold management.

Acceptance Criteria
Creating a New Threshold
Given an authorized manager is on the Threshold Configuration Interface When the manager enters a valid numeric wait-time value into the input field and clicks "Save" Then the system displays a success message and shows the new threshold in the list with the correct value And the new threshold is immediately available across all relevant modules
Editing an Existing Threshold
Given an existing wait-time threshold is listed When the manager adjusts the slider control or numeric input and clicks "Update" Then the system confirms the change with a success notification And modules using the threshold reflect the updated value without requiring a page reload
Validation of Input Range
Given the manager enters a wait-time value below the minimum or above the maximum allowed range When the manager attempts to save the threshold Then the system highlights the invalid field in red and displays an inline validation error message And the "Save" button remains disabled until a valid value is entered
Using Preset Templates
Given a set of preset threshold templates is available When the manager selects a preset template from the dropdown Then the threshold fields auto-populate with the template values And the manager can review and confirm by clicking "Apply Template" And the applied template is saved as a custom threshold
Real-time Application Across Modules
Given a threshold value has been created or edited When the manager navigates to the Scheduling or Patient Flow module within 5 seconds Then alerts for appointments exceeding the configured wait-time display based on the new threshold
Department-Level Threshold Settings
"As a practice manager, I want to configure wait-time thresholds for individual departments so that alerts match each department’s typical processing time and reduce unnecessary notifications."
Description

The system shall allow managers to assign distinct wait-time thresholds for each clinical department (e.g., reception, triage, consultation, billing). Each department setting can be adjusted independently to reflect varying operational workflows and patient flow patterns. The configuration persists per department and feeds into real-time monitoring and alert modules, enabling precise identification of bottlenecks at the departmental level and reducing false-positive alerts.

Acceptance Criteria
Initial Department Threshold Configuration
Given the manager is on the Threshold Tuner page and selects the 'Triage' department, When they input a wait-time value of 15 minutes and click 'Save', Then the system stores the threshold and displays a confirmation message 'Threshold updated successfully'.
Threshold Persistence After Logout
Given the manager has set a 20-minute threshold for the Consultation department, When they log out and log back in, Then the previously saved 20-minute threshold is displayed for Consultation.
Threshold Validation Prevents Invalid Input
Given the manager attempts to set a negative or non-numeric wait time in the Billing department, When they click 'Save', Then the system rejects the input and displays an inline error 'Please enter a valid positive number in minutes'.
Real-Time Alert Trigger on Threshold Breach
Given a patient wait time in Reception exceeds the configured 10-minute threshold, When the live monitoring module evaluates wait times, Then the system generates a 'Wait time exceeded' alert tagged 'Reception' and logs the event with a timestamp.
Independent Department Adjustment
Given thresholds are set for Reception (5 mins) and Triage (10 mins), When the manager updates only the Reception threshold to 8 minutes and saves changes, Then the Triage threshold remains at 10 minutes and only Reception is updated.
Appointment-Type Threshold Settings
"As a practice manager, I want to set wait-time thresholds for each appointment type so that alerts consider the varying durations of different visit types and avoid confusion."
Description

The system shall support threshold customization based on different appointment types (e.g., new patient, follow-up, lab test), allowing managers to define wait-time limits for each category. This feature integrates with the scheduling module to automatically apply the correct threshold based on appointment metadata. It ensures that threshold alerts are contextually relevant, improving alert accuracy and helping staff focus on genuine delays.

Acceptance Criteria
Set Threshold for New Patient Appointment
Given the manager selects "New Patient" from the appointment-type list and enters a wait-time threshold of 20 minutes When the manager saves the setting Then the system stores the threshold and displays a confirmation message
Apply Threshold to Scheduled Appointments
Given an active "New Patient" appointment exists with a wait-time threshold of 20 minutes When the patient's wait time exceeds 20 minutes Then the dashboard displays an alert for that appointment
Edit Existing Appointment-Type Threshold
Given the manager navigates to the threshold settings for "Follow-Up" appointments When the manager changes the threshold from 10 to 15 minutes and saves Then the system updates the threshold and applies it to all subsequent follow-up appointments
Remove Threshold for Lab Test
Given the manager clears the threshold value for "Lab Test" appointments When the manager saves the empty setting Then the system reverts to the default wait-time threshold and displays the default value
Threshold Integration with Scheduling Module
Given a new appointment is created with type metadata "New Patient" When the appointment is added to the schedule Then the system automatically applies the configured threshold for "New Patient" appointments to that entry
Threshold Value Validation and Error Handling
"As a practice manager, I want the system to warn me of invalid threshold values so that I can only save sensible thresholds and avoid configuration errors."
Description

The system shall enforce validation rules on threshold inputs, ensuring values fall within acceptable ranges (e.g., minimum 1 minute, maximum 240 minutes). Invalid entries trigger inline error messages and prevent saving until corrected. This mechanism ensures data integrity, prevents extreme configurations that could disrupt alerting logic, and guides users toward valid settings.

Acceptance Criteria
Valid Threshold Input for Department Wait Times
Given a manager is on the Threshold Tuner settings page When they enter a value between 1 and 240 in the wait-time threshold field Then the input is accepted without errors and can be saved.
Threshold Input Below Minimum Allowed
Given a manager enters a wait-time threshold of 0 or a negative number When they move focus away from the input field Then an inline error message 'Value must be at least 1 minute' is displayed and saving is disabled.
Threshold Input Above Maximum Allowed
Given a manager enters a wait-time threshold greater than 240 When they move focus away from the input field Then an inline error message 'Value cannot exceed 240 minutes' is displayed and saving is disabled.
Non-Numeric Threshold Input Handling
Given a manager enters a non-numeric character in the wait-time threshold field When they move focus away from the input field Then an inline error message 'Please enter a valid number' is displayed and saving is disabled.
Successful Save of Valid Threshold Values
Given all department and appointment type thresholds are within the valid range When the manager clicks the 'Save' button Then the system saves the new thresholds, displays a confirmation message 'Thresholds updated successfully', and no validation errors are shown.
Real-Time Threshold Breach Alerts
"As a practice manager, I want to receive real-time alerts when wait times exceed thresholds so that I can promptly address delays and maintain patient satisfaction."
Description

The system shall monitor live patient flow data against configured thresholds and generate in-app and optional push notifications when wait times exceed set limits. Alerts must include contextual details such as department, appointment type, current wait time, and threshold value. The alerting mechanism integrates with the existing notification center and supports acknowledgement workflows to track resolution.

Acceptance Criteria
Live Monitoring Trigger for Exceeded Threshold
Given a wait-time threshold is configured for a department and appointment type, when the system receives real-time patient flow data and the current wait time exceeds the configured threshold, then the system must generate an alert entry in the notification center within 5 seconds.
In-App Notification Content Display
Given an alert has been generated for a threshold breach, when a manager views the notification center in the Pulseboard dashboard, then each alert must display department, appointment type, current wait time, threshold value, and timestamp.
Push Notification Delivery
Given a manager has enabled push notifications and a threshold breach occurs, when the system generates the alert, then the push notification must be delivered to the manager’s device within 10 seconds and include department, appointment type, current wait time, and threshold value.
Alert Acknowledgement Workflow Tracking
Given an active threshold breach alert is visible in the notification center, when the manager acknowledges the alert, then the system must mark the alert as acknowledged, record the user ID and acknowledgement timestamp, and remove it from the active alert list.
Threshold Configuration Update Impact
Given a manager updates the wait-time threshold for a department or appointment type, when the update is saved, then the system must immediately apply the new threshold to live monitoring and only generate alerts based on the updated value.
Threshold Change Audit Log
"As an administrator, I want to review a history of threshold changes so that I can track adjustments, understand decision drivers, and ensure compliance."
Description

The system shall maintain an audit log for all threshold configuration changes, capturing details such as timestamp, user ID, previous and new values, and change reason. The log should be viewable within the administration section and support filtering by date, user, and department or appointment type. This ensures accountability, enables historical analysis of threshold adjustments, and supports compliance and best practices.

Acceptance Criteria
Pediatric Department Threshold Update
Given an admin user on the Threshold Tuner settings page and selects "Pediatric" department, When the user changes the wait-time threshold from 15 to 20 minutes and enters "Increase due to higher patient volume" as the change reason and saves, Then an audit log entry is created capturing the user ID, timestamp, previous value "15", new value "20", department "Pediatric", and change reason.
Physical Therapy Appointment Threshold Adjustment
Given a practice manager accesses the Threshold Tuner settings and chooses the "Physical Therapy" appointment type, When they modify the threshold from 30 to 25 minutes with reason "Optimize schedule flow" and confirm, Then the system logs an entry with the manager’s user ID, timestamp, old value "30", new value "25", appointment type "Physical Therapy", and provided reason.
Filter Audit Logs by Date Range
Given an admin is in the administration audit log section, When they set filters for logs between 2025-05-01 and 2025-05-31 and apply, Then the displayed log entries all have timestamps within that date range.
Filter Audit Logs by User
Given an administrator in the audit log view, When they select user ID "USR123" as a filter and apply, Then only audit entries where the user ID equals "USR123" are shown.
Filter Audit Logs by Department and Appointment Type
Given a compliance officer in the audit log interface, When they choose department "Cardiology" and appointment type "Follow-up" filters and apply, Then the system lists only audit entries matching both department "Cardiology" and appointment type "Follow-up".

Crowd Mapper

Generates a live, color-coded heatmap of clinic areas, enabling managers to visualize high-traffic zones instantly and deploy resources where they’re needed most.

Requirements

Real-time Traffic Heatmap
"As a practice manager, I want to see a live heatmap of patient movement so that I can quickly identify and address overcrowded areas."
Description

Render a live, color-coded map overlay displaying current foot traffic density across predefined clinic areas, updating seamlessly as new sensor data is received to enable instant visualization of congestion hotspots.

Acceptance Criteria
Initial Heatmap Load
Given the clinic manager opens the Pulseboard dashboard, When the Real-time Traffic Heatmap component loads, Then the heatmap must render within 2 seconds, display all predefined clinic areas, and use the correct base color (grey) for zones with no current sensor data.
Sensor Data Update
Given new foot traffic sensor data is received, When the data is processed by the system, Then the heatmap must update the color of only the affected zones within 5 seconds, without requiring a full page refresh.
High-Traffic Alert Highlight
Given a predefined foot traffic density threshold is exceeded for any clinic area, When the system detects the threshold breach, Then the corresponding zone color must transition to alert red and display an alert icon overlay in the zone.
No Data Fallback
Given a sensor has not sent data for 30 seconds or more, When the heatmap is next refreshed, Then the corresponding zone must change to grey and show a tooltip label stating "No data available" on hover.
Data Accuracy Validation
Given the backend API provides foot traffic density values, When the heatmap displays the data, Then each zone’s displayed density color code must accurately reflect the API values within a ±5% tolerance.
Custom Zone Configuration
"As a practice manager, I want to define custom zones on the floor plan so that the heatmap reflects the unique layout of my clinic."
Description

Provide an interface for administrators to define, edit, and group specific clinic zones or subareas, allowing tailored monitoring and precise tracking of traffic in areas that match their operational workflows.

Acceptance Criteria
Creating a New Custom Zone
Given an administrator is on the Custom Zone Configuration page When they click 'Add Zone' and draw a polygon on the clinic map Then a new zone named 'Zone X' is created with the specified boundaries and appears in the zone list; And a confirmation message 'Zone created successfully' is displayed.
Editing an Existing Custom Zone
Given an administrator selects an existing zone named 'Front Desk' When they modify its boundaries via drag handles and click 'Save' Then the zone updates on the map with the new boundaries and the zone list reflects the changes; And a confirmation message 'Zone updated successfully' is displayed.
Grouping Custom Zones
Given an administrator has created multiple zones When they select two or more zones and click 'Create Group' Then a new group named 'Group Y' is created containing the selected zones; And the group appears in the group list with an option to expand and view member zones; And the heatmap filter can be applied to the group as a single unit.
Preventing Overlapping Zones
Given an administrator attempts to create or edit a zone that overlaps an existing zone When they click 'Save' Then the system prevents the action and displays an error message 'Zones cannot overlap'; And it highlights the overlapping area in red on the map.
Deleting a Custom Zone
Given an administrator selects a zone named 'Waiting Area' When they click 'Delete' and confirm the deletion Then the zone is removed from the map and the zone list; And a confirmation message 'Zone deleted successfully' is displayed; And any heatmap data associated with the zone is archived.
Dynamic Color Thresholds
"As a practice manager, I want to customize traffic thresholds so that the color-coding accurately represents congestion relative to my clinic’s capacity."
Description

Enable users to set and adjust threshold levels for low, medium, and high traffic, automatically applying corresponding color codes on the heatmap to reflect real-time status and accommodate varying clinic capacities.

Acceptance Criteria
Adjust Low Traffic Threshold for Morning Peak
Given the clinic manager is on the Crowd Mapper settings page and viewing traffic threshold controls When the manager inputs a new low-traffic threshold value (e.g., from 10 to 20) Then the heatmap updates zones with occupancy below the new threshold to the defined low traffic color within 5 seconds And the new threshold is saved and persists across page reloads
Update Medium Traffic Threshold for Special Event
Given a scheduled event increasing patient volume When the admin updates the medium-traffic threshold from the default to a higher value Then all zones with occupancy between the updated low and medium values display the medium traffic color in real time And a confirmation message 'Thresholds updated successfully' appears
Automatic High Traffic Color Change on Threshold Breach
Given the system is monitoring live patient counts When a zone’s patient count crosses the high traffic threshold Then the zone’s color changes to the high traffic color within 2 seconds And an alert icon appears on the zone
Reset Thresholds to Default
Given custom thresholds have been set When the manager selects 'Reset to Default' thresholds Then all thresholds revert to the system defaults And the heatmap colors update accordingly within 5 seconds
Persist Custom Thresholds Across Sessions
Given custom thresholds have been saved When the manager logs out and logs back in Then the previously defined thresholds are loaded and applied to the heatmap And the threshold settings page displays the saved values
Real-time Alert Notifications
"As a practice manager, I want to receive alerts when an area becomes overcrowded so that I can redeploy staff or resources promptly."
Description

Implement a notification system that triggers alerts when traffic in any zone exceeds defined thresholds, delivering in-app pop-ups or optional email/SMS messages to prompt immediate managerial action.

Acceptance Criteria
In-App Alert Display
Given a zone's live patient count exceeds the configured threshold, When the system detects the threshold breach, Then an in-app pop-up notification is displayed within 5 seconds, And the notification includes the zone name, threshold value, and current count.
Email Alert Dispatch
Given a user has enabled email notifications for a specific zone, When that zone's patient count exceeds the threshold, Then the system queues and sends an email notification within 1 minute, And the email contains the zone name, breach timestamp, and an actionable link.
SMS Alert Dispatch
Given a user has enabled SMS notifications for a specific zone, When that zone's patient count exceeds the threshold, Then the system sends an SMS alert within 1 minute, And the SMS message includes the zone name and a concise breach summary within 160 characters.
User Preference Enforcement
Given a user updates their notification preferences, When the update is saved, Then subsequent threshold breaches only trigger notifications via the enabled channels, And notifications are not sent through any disabled channels.
Alert Acknowledgment Logging
Given a notification is displayed in-app, emailed, or sent via SMS, When a user acknowledges the alert through the dashboard, Then the acknowledgment is logged with user ID, timestamp, and alert ID, And the log entry is retrievable via the system audit interface.
Historical Traffic Trends
"As a practice manager, I want to review past traffic patterns so that I can optimize staff scheduling and improve clinic efficiency."
Description

Store and visualize historical traffic data by zone, offering time-series charts and heatmap playback to analyze peak hours, recurring patterns, and resource utilization trends over selected date ranges.

Acceptance Criteria
Viewing Historical Traffic for a Specific Zone
Given a clinic manager selects the 'North Wing' zone and the date range 2025-06-01 to 2025-06-07, when the manager submits the request, then the system displays a time-series chart showing hourly patient counts for each day with values accurate to within ±1%.
Heatmap Playback of Historical Traffic
Given a selected date of 2025-05-15, when the manager initiates playback, then the live heatmap animates traffic density changes in ten-minute intervals with color intensities reflecting recorded counts and provides responsive play, pause, and time-slider controls.
Comparing Traffic Trends Across Two Date Ranges
Given the manager selects date ranges 2025-01-01 to 2025-01-07 and 2025-02-01 to 2025-02-07, when the comparison view is applied, then the system displays side-by-side time-series charts highlighting differences in peak hours and daily counts with percentage change annotations.
Filtering Historical Data by Day of Week and Time of Day
Given the manager applies filters for weekdays only and hours between 09:00 and 17:00, when filters are applied, then the time-series charts and heatmap visualizations update to show only filtered data and corresponding summary statistics adjust accordingly.
Exporting Historical Traffic Data
Given the manager requests an export for 'East Wing' from 2025-05-01 to 2025-05-31, when the export is generated, then the system provides a downloadable CSV file containing zone, timestamp, and traffic count with filename 'traffic_trends_EastWing_20250501_20250531.csv'.

Predictive Pulse

Uses historical and real-time data to forecast potential bottlenecks before they occur, empowering managers to proactively adjust staffing and schedules to maintain smooth patient flow.

Requirements

Historical Data Integration
"As a practice manager, I want Pulseboard to import my clinic’s historical scheduling and patient flow data so that the system can learn from past patterns and improve forecast accuracy."
Description

Enable Pulseboard to import and normalize historical scheduling, billing, and patient flow records from existing systems into a unified data store, ensuring consistent formats and data quality. This requirement supports trend analysis and model training by providing a reliable foundation of past performance metrics.

Acceptance Criteria
Bulk Historical Data Import from CSV Files
Given an admin user has valid CSV exports of scheduling, billing, and patient flow records When the user uploads these files via the import interface Then the system ingests all records without error And mapping prompts ensure each data column is correctly mapped to the unified data store fields And the import summary report displays total records ingested, errors, and warnings
API-based Data Retrieval and Ingestion
Given the admin configures API credentials for an existing EMR system When the system fetches historical data via scheduled API calls Then the system retrieves records for the specified date range And data is normalized to match the unified schema And logs detail the number of records retrieved and any failures
Data Normalization and Format Standardization
Given imported records have inconsistent date formats and units When the normalization process is executed Then all date fields are converted to ISO 8601 format And numeric fields (e.g., billing amounts) are formatted to two decimal places And patient identifiers are validated against the unified ID schema
Duplicate Record Detection and Resolution
Given the unified data store contains records from multiple sources When new data is imported Then the system detects potential duplicates based on patient ID and timestamp proximity And flags duplicates for manual review or automatically merges based on predefined rules And generates a report of merged and excluded records
Performance Benchmarking for Large Data Sets
Given a historical dataset exceeding 1 million records When the import and normalization process runs Then the system completes ingestion within 30 minutes And CPU and memory usage remain below defined service thresholds And the system remains responsive for concurrent user operations
Real-time Data Streaming
"As a practice manager, I want Pulseboard to process live clinic events in real time so that predictions reflect the latest operational status and trends."
Description

Implement real-time ingestion of scheduling updates, patient check-ins, and billing events through secure APIs, processing incoming data streams with low latency. This continuous data flow enables up-to-the-minute visibility into clinic operations, feeding the predictive engine with current state information.

Acceptance Criteria
Secure API Connection
Given valid and unexpired API credentials, when the system initiates the data streaming connection, then the connection uses TLS 1.2 or higher and is established within 2 seconds; unauthorized credential attempts return a 401 error; connection parameters match the API specifications.
Scheduling Update Ingestion
Given a scheduling update event occurs, when the update is received by the API, then the system ingests and writes the event to the data store within 1 second; the record fields match the incoming payload schema; no data loss is detected.
Patient Check-In Processing
Given a patient check-in event is sent, when the event reaches the streaming endpoint, then the system processes and acknowledges the event within 500ms; the patient status is updated in the dashboard within 1 second; if processing fails, the system retries up to 3 times and logs the failure.
Billing Event Stream Handling
Given a billing transaction event arrives, when ingesting into the stream, then the event is validated against the billing schema; invalid events are rejected with a descriptive error logged; valid events are processed and reflected in the billing dashboard within 1 second.
Low Latency End-to-End Monitoring
Given real-time data streaming is active, when end-to-end monitoring is enabled, then the system measures and records latency between source ingestion and dashboard update; latency does not exceed 2 seconds 99% of the time; alerts are generated if the latency threshold is breached.
Bottleneck Prediction Model
"As a practice manager, I want Pulseboard to predict upcoming bottlenecks in patient flow so that I can proactively adjust staffing and schedules to prevent delays."
Description

Develop and train a machine learning model that analyzes combined historical and real-time data to forecast potential patient flow and resource bottlenecks up to four hours ahead. The model should support adjustable thresholds, incorporate seasonality and staffing variables, and achieve at least 85% prediction accuracy in pilot tests.

Acceptance Criteria
Forecast Generation Within SLA
Given real-time historical and current data is available, when the model is triggered, then the forecast for the next four hours is returned within 5 seconds.
Forecast Accuracy Validation
When tested on pilot datasets, the model achieves at least 85% prediction accuracy measured by mean absolute percentage error (MAPE) ≤15%.
Threshold Adjustment Functionality
Given a user-defined threshold between 0% and 100%, when the threshold is adjusted in 5% increments, then the model updates predictions accordingly within 2 seconds.
Incorporation of Seasonality and Staffing Variables
When generating forecasts, the model accounts for time-of-day, day-of-week, seasonal trends, and current staffing levels, validated by feature importance scores ≥5% for each variable.
Model Robustness Under Data Anomalies
Given datasets with up to 10% missing or noisy entries, when the model is run, then it maintains prediction accuracy ≥80% on anomaly-augmented test sets.
Proactive Alert System
"As a practice manager, I want to receive automated alerts when Pulseboard forecasts bottlenecks so that I can take immediate action to maintain smooth clinic operations."
Description

Design an alert mechanism that triggers notifications via the dashboard, email, or SMS when predicted bottleneck risks exceed predefined thresholds. Notifications should include actionable insights, recommended mitigation steps, and relevant data context to support quick decision-making.

Acceptance Criteria
Dashboard Bottleneck Alert
Given a predicted bottleneck risk exceeds the visual threshold; When the manager accesses the Pulseboard dashboard; Then a red visual alert indicator appears on the affected clinic module showing the risk percentage, expected delay duration, and pinpointed patient flow metric.
Email Notification for Staffing Alert
Given a predicted staffing-related bottleneck risk surpasses the predefined email threshold; When the system detects this condition; Then an email is sent within 2 minutes to the manager’s registered address containing the risk percentage, impacted department, and a recommended staffing adjustment plan.
SMS Alert for High-Risk Bottleneck
Given a predicted bottleneck risk exceeds the critical SMS threshold; When the alert is triggered; Then an SMS is delivered within 1 minute to the manager’s configured phone number with a concise summary of the risk, time of occurrence, and a link to detailed dashboard insights.
Actionable Insights Content
Given an alert is generated; When the manager views the notification details; Then the notification content includes at least two recommended mitigation steps, relevant historical performance comparisons, and projected impact metrics.
Threshold Configuration Change Notification
Given an administrator updates the bottleneck risk threshold value; When the new threshold is saved; Then the system displays a confirmation message on the dashboard and sends an email within 5 minutes confirming the updated threshold and its effective date.
Automated Scheduling Suggestions
"As a practice manager, I want Pulseboard to suggest optimal schedule adjustments based on predicted bottlenecks so that I can efficiently balance staffing levels without manual analysis."
Description

Build a recommendation engine that translates forecasted bottlenecks into specific staffing or schedule adjustments. Suggestions should factor in staff availability, skill sets, and patient priorities, offering one-click schedule modifications that can be reviewed and approved by managers.

Acceptance Criteria
Overcapacity Alert Resolution
Given the system predicts a bottleneck in the appointment queue, When the recommendation engine runs, Then it suggests staffing adjustments that ensure predicted wait times remain under 10 minutes and covers all scheduled appointments.
Skill-Based Staff Allocation
Given a forecasted increase in specialty cases (e.g., radiology), When generating scheduling suggestions, Then the engine assigns available staff with the required specialty certifications to peak time slots.
High-Priority Patient Surge
Given a predicted surge of high-priority (emergency) patients, When the recommendation engine executes, Then it recommends reallocating at least two triage nurses to available shifts within the next 30 minutes.
Last-Minute Staff Unavailability
Given a staff member marks themselves unavailable less than 2 hours before their shift, When the engine recalculates schedule suggestions, Then it offers at least three alternative staff options with matching skills and availability.
One-Click Schedule Adjustment
Given the manager reviews suggested adjustments, When they click “Apply Suggestions”, Then the system updates the schedule in real time, sends notifications to affected staff, and updates patient flow forecasts accordingly.

Staff Signal

Enables one-click notifications to on-shift or on-call staff via SMS or in-app messages when wait times exceed safe limits, ensuring rapid response to crowded areas.

Requirements

Real-Time Wait Time Monitoring
"As a practice manager, I want the system to display up-to-date patient wait times so that I can identify and address delays before they escalate."
Description

The system continuously tracks and updates patient wait times across all clinic areas in real time, feeding this data to Pulseboard’s dashboard to detect when wait times exceed safe limits. It provides accurate, up-to-the-second metrics for managers, ensuring timely awareness of bottlenecks. It integrates with scheduling and patient flow modules to pull live data and supports threshold triggers. Expected outcome: immediate visibility into wait time spikes, enabling proactive staff management and reduced patient complaints.

Acceptance Criteria
Continuous Wait Time Tracking
Given the system is connected to patient check-in, when a patient checks in, then the dashboard displays the patient's wait time and increments it every minute, with updates reflected within one second of each minute.
Threshold Exceeded Detection
Given a wait time threshold of 30 minutes is configured, when any patient's wait time exceeds 30 minutes, then the system flags that patient's entry in red within five seconds of the threshold breach.
Automated Staff Signal Notification
Given a wait time threshold breach is detected, when the breach occurs, then the system sends an SMS and in-app notification to on-duty staff within ten seconds, including patient location and current wait time.
Data Synchronization with Patient Flow Module
Given real-time updates in the patient flow module, when a patient's status changes, then the wait time tracking reflects the new status on the dashboard within two seconds.
Dashboard Visualization Accuracy
Given multiple clinic areas (waiting room, consultation rooms), when displaying wait times, then the dashboard shows average, median, and longest wait times per area updated in real time with an error margin below 1%.
Customizable Threshold Settings
"As a clinic administrator, I want to set custom wait time thresholds so that alerts reflect our specific operational needs."
Description

This requirement allows admins to define and adjust wait time thresholds for different clinic areas and appointment types within the dashboard. It offers a user-friendly interface to set safe upper limits, ensuring that notifications only trigger when genuinely needed. Thresholds can be configured per location, service type, or time of day. Integrates with monitoring and notification systems to activate Staff Signal only under authorized conditions, minimizing false alerts.

Acceptance Criteria
Set Threshold for Clinic Area
Given an authenticated admin navigates to the dashboard’s Threshold Settings, when they enter a valid wait time value and select a clinic area then click Save, then the new threshold is persisted, displayed in the list, and retrievable via the API.
Trigger Notification on Threshold Breach
Given a threshold of X minutes is configured for Area A, when real-time monitoring records a wait time that exceeds X minutes, then the Staff Signal notification is dispatched to on-shift and on-call staff within 30 seconds.
Configure Time-of-Day Specific Threshold
Given an admin sets distinct wait time thresholds for peak hours (08:00–10:00) and off-peak hours for Service Z, when the current time falls in peak hours and the wait time exceeds the peak threshold, then the notification uses the correct threshold; and when it exceeds the off-peak threshold outside peak hours, then it triggers accordingly.
Edit Existing Threshold
Given an existing threshold entry for Service Y, when an admin updates its value and saves changes, then the updated threshold replaces the previous value and is immediately used for subsequent wait-time evaluations.
Delete Threshold and Suppress Alerts
Given a threshold for Area B no longer needed, when an admin deletes the threshold entry and confirms deletion, then no notifications are triggered for that area when wait times exceed the former threshold.
One-Click Staff Notification
"As a practice manager, I want to alert available staff with one click when wait times are high so that additional support arrives quickly."
Description

Enables managers to send notifications to on-shift or on-call staff with a single click when thresholds are breached. The interface displays available staff and default notification templates. Once triggered, it dispatches messages and logs the event. This seamless action reduces response time and simplifies urgent communication during peak periods.

Acceptance Criteria
Threshold Breach Notification Initiation
Given clinic wait time exceeds the configured safe limit When the manager clicks the “Notify Staff” button Then the notification modal displays all on-shift and on-call staff along with default message templates
Default Template Auto-Selection
Given the notification modal is opened When staff are listed Then the default notification template is preselected and editable by the manager
Successful Dispatch of Notification
Given the manager has selected staff and confirmed the message When the manager clicks “Send” Then SMS and in-app notifications are dispatched within 5 seconds and a success confirmation appears
Event Logging of Notifications
When a notification is successfully sent Then the system logs an entry with timestamp, manager ID, staff IDs, and template ID, and the entry is viewable in the notification audit log
Dispatch Failure and Retry Fallback
Given an SMS dispatch failure When the system detects the failure Then it retries up to 3 times and, if unsuccessful, sends an in-app notification fallback and alerts the manager of the failure
Multi-Channel Delivery (SMS and In-app)
"As on-call staff, I want to receive alerts through SMS or in-app messages so that I never miss urgent notifications."
Description

Implements dual channels for sending alerts via SMS and in-app notifications, ensuring messages reach staff regardless of their current platform. It leverages third-party SMS gateways and in-app messaging API. Supports fallback logic: if the in-app notification isn't read within a set timeframe, an SMS is sent. This redundancy ensures critical alerts are not missed.

Acceptance Criteria
In-App Notification Read Confirmation
Given a staff member is on shift and has the Pulseboard app open, When the wait time for any patient exceeds the predefined safe limit, Then the system sends an in-app notification immediately; And the notification appears in the staff member’s notification center; And the notification includes the alert type, clinic area, and timestamp.
Fallback to SMS After Timeout
Given an in-app notification is sent and not marked as read within 2 minutes, When the timeout elapses, Then the system sends an SMS containing the same alert details to the staff member’s registered phone number; And the event is logged as a fallback notification.
Dual Channel Delivery Verification
Given the wait-time alert is triggered, When the staff member is eligible for both channels, Then the system attempts to deliver the notification via both SMS and in-app message; And records delivery status and timestamps for each channel; And flags any failures.
SMS Gateway Failure Handling
Given the third-party SMS gateway returns an error or timeout, When the SMS attempt fails, Then the system retries up to two additional times at 30-second intervals; And if still unsuccessful, logs the failure and sends an error alert to the admin dashboard.
Notification Logging and Auditing
Given any notification attempt (in-app or SMS), When the notification is sent or fails, Then the system logs the channel, delivery status, timestamp, recipient ID, and alert details; And provides a queryable audit trail in the admin interface.
Notification Acknowledgment and Tracking
"As a practice manager, I want to see which staff have acknowledged an alert so that I can confirm coverage and follow up if needed."
Description

After dispatch, notifications include an acknowledgment mechanism for staff to confirm receipt. The system tracks responses, updates the dashboard with who has acknowledged, and sends reminders if no acknowledgment is received within a configurable interval. This ensures accountability and visibility into response rates.

Acceptance Criteria
Staff Receives Notification and Acknowledges It
Given a wait time threshold is exceeded When the system sends a notification to on-shift staff Then staff can click an acknowledgment button within 2 minutes And the system records the acknowledgment timestamp
Dashboard Reflects Acknowledgment Status
Given a notification has been acknowledged When the acknowledgment is received Then the dashboard displays the staff member’s name and acknowledgment time next to the corresponding notification
Automated Reminder for Unacknowledged Notifications
Given no acknowledgment is received within the configured interval When the interval elapses Then the system sends a reminder notification to the staff member and logs the reminder event
Configurable Acknowledgment Interval Setting
Given an administrator configures the acknowledgment interval to 5 minutes When a notification is dispatched Then the reminder is scheduled to send exactly 5 minutes after the initial notification
Tracking Multiple Notifications and Responses
Given multiple notifications are dispatched to different staff members When acknowledgments are received at varying times Then the dashboard lists each notification with its individual acknowledgment status and timestamp
Staff Availability Management
"As a staff member, I want to update my on-call status easily so that I receive relevant alerts only when I’m available."
Description

Provides a module for staff to update their on-shift and on-call statuses in real time. The dashboard reflects current availability and contact preferences. Integrates with scheduling module to auto-populate shifts. Ensures notifications target the correct subset of staff and reduces manual coordination.

Acceptance Criteria
Real-Time Shift Status Update
Given a staff member is logged into Pulseboard, When they toggle their status to 'On Shift', Then the dashboard displays their name in the Active Staff list within 5 seconds.
Auto-Populate Upcoming Shifts
Given the scheduling module has a staff shift scheduled for the current day, When the day begins at 00:00, Then the staff's on-shift status auto-populates to 'On Shift' and a prompt notification appears.
Targeted Notifications Delivery
Given wait times exceed the safe threshold, When the 'Send Staff Signal' action is initiated, Then SMS and in-app messages are delivered only to staff members with status 'On Shift' or 'On Call' according to their contact preferences.
Contact Preference Respect
Given a staff member has selected SMS as their preferred contact method, When a Staff Signal notification is sent, Then the system sends an SMS and suppresses other notification channels for that staff member.
Dashboard Availability Refresh
Given a staff member updates their on-call or on-shift status, When the status change is saved, Then the dashboard refreshes automatically without a full page reload and reflects the update within 3 seconds.

Patient Notify

Automatically sends personalized SMS or app alerts to patients when delays are expected, improving transparency, reducing no-shows, and enhancing overall satisfaction.

Requirements

Delay Detection Algorithm
"As a practice manager, I want the system to automatically detect appointment delays so that I can notify patients promptly and reduce waiting-time complaints."
Description

Monitor appointment schedules in real-time by integrating with the scheduling module, calculate expected start times, and automatically detect when an appointment is running behind its scheduled start by a configurable threshold. Upon detection, trigger the notification workflow to inform affected patients about delay estimates.

Acceptance Criteria
Delay Threshold Exceeded
Given an appointment scheduled at 10:00 AM with a 15-minute delay threshold When the actual start time surpasses 10:15 AM Then an SMS containing the delay estimate is sent to the patient's phone within 60 seconds
No Notification for Minor Delays
Given an appointment scheduled with a 10-minute threshold When the start time is delayed by less than or equal to 10 minutes Then no notification is sent to the patient
Threshold Configuration Update Applied
Given an administrator updates the delay threshold to a new value When the change is saved in the system Then subsequent delay detections use the updated threshold without requiring a system restart
Scheduling Module Integration Recovery
Given the scheduling module experiences a connection outage When the connection is restored Then the delay detection algorithm resumes monitoring and processes backlog data within 5 minutes
Batch Notifications for Concurrent Delays
Given multiple appointments in the same time slot exceed the delay threshold When delays are detected Then individual notifications are sent to all affected patients within 2 minutes of detection
Personalized Message Composition
"As a clinic administrator, I want to send personalized delay messages so that patients feel informed and valued even when appointments run late."
Description

Generate customizable SMS and app notification templates that dynamically incorporate patient name, appointment details, expected delay duration, and personalized greetings. Allow administrators to configure message variables and language preferences to ensure clear and empathetic communication.

Acceptance Criteria
Delay Notification Template Customization
When an administrator adds or edits a notification template, they can insert and label placeholders for patient name, appointment date/time, and delay duration; upon saving, the custom content and placeholders persist and are available for future messages.
Dynamic Variable Insertion into Messages
Given a patient scheduled for a delayed appointment, when the notification is triggered, then the outgoing SMS or app alert includes the correct patient name, original appointment time, and specified delay duration in the message body.
Language Preference Application
Given a patient with Spanish set as their preferred language, when a delay notification is sent, then the template is rendered entirely in Spanish with all dynamic variables correctly populated.
Message Preview Accuracy
When an administrator previews a notification before sending, the preview displays the exact message text with real patient data—name, appointment details, and delay duration—in the selected language and greeting style.
Default Greeting Selection
When configuring a notification template, the administrator can select a greeting style (e.g., “Dear” vs. “Hi”) and the chosen greeting is correctly applied in all generated messages.
Multi-Channel Notification Delivery
"As a patient, I want to receive delay notifications via my preferred channel (SMS or app) so that I can stay updated even if one channel is unavailable."
Description

Integrate with both SMS gateways and in-app push notification services to deliver alerts through the patient's preferred channel. Ensure reliable message delivery by implementing retry mechanisms, delivery status checks, and fallback options if the primary channel fails.

Acceptance Criteria
SMS Preferred Channel Delivery
Given a patient with SMS as their preferred channel and a delay of more than 5 minutes is recorded, when the system registers the delay, then it must send a personalized SMS within 1 minute and mark the status as 'Sent'.
App Push Preferred Channel Delivery
Given a patient with in-app push notifications enabled and a delay of more than 5 minutes occurs, when the delay is detected, then the system must deliver a personalized push notification within 1 minute and update the status to 'Delivered'.
Primary Channel Failure Fallback
Given a notification attempt on the primary channel fails and returns an error code, when 3 retry attempts also fail, then the system must automatically send the notification via the secondary channel within 2 minutes of the initial failure.
Notification Retry Mechanism
Given a transient network error occurs during delivery, when the initial send attempt fails, then the system must retry sending up to 3 times at exponential backoff intervals (1, 2, and 4 minutes), and log each retry attempt.
Delivery Status Validation
Given any notification is sent (via SMS or push), when the delivery status changes (e.g., Delivered, Failed, Pending), then the system must update the delivery status in the dashboard within 30 seconds of receiving the status from the gateway.
Opt-in/Opt-out Preferences Management
"As a patient, I want to choose my notification preferences so that I receive alerts only when I consent and at times that suit me."
Description

Provide a user interface for patients to manage their notification preferences, including opting in or out of SMS and app alerts and selecting preferred notification times. Sync preferences with the patient database and enforce consent to comply with privacy regulations.

Acceptance Criteria
Access Preferences Page
Given a registered patient is logged into the patient portal When they navigate to the Notification Preferences section Then the system displays options to opt in or out of SMS and app alerts and to select preferred notification times
Update Notification Channels
Given a patient is on the Notification Preferences page When they toggle SMS or app alerts on or off Then their selection is saved and a confirmation message is displayed
Set Preferred Notification Time Window
Given a patient opts in to receive alerts When they select a time window for notifications Then the system only sends notifications within the specified window and shows the saved time range on the preferences page
Sync Preferences with Database
Given a patient updates their notification preferences When the changes are saved Then the database reflects the updated opt-in/opt-out status and notification times within one second
Consent Enforcement on New Registrations
Given a new patient completes account registration When they reach the notification preferences step Then the system requires explicit opt-in consent before allowing them to proceed and does not send any alerts without consent
Notification Tracking and Logging
"As a practice manager, I want to review notification history so that I can audit communication effectiveness and address any delivery issues."
Description

Log all sent notifications with timestamps, delivery status, channel used, and message content. Provide reporting tools for administrators to review notification history, audit communication performance, and identify delivery failures for follow-up actions.

Acceptance Criteria
Notification Logging Accuracy
Given a notification is sent, when the system logs the notification, then the log entry must include timestamp, delivery status, channel used, and message content matching the sent notification.
Notification History Access
Given an administrator accesses the notification reporting tool, when they select a date range, then the system displays all notifications sent within that range in chronological order.
Delivery Failure Identification
Given there are notifications with status 'Failed', when an administrator runs the failure audit report, then all failed notifications are listed with patient ID and failure reason for follow-up.
Notification Log Export
Given an administrator requests to export notification logs, when they choose export as CSV, then the system generates a file containing all log fields for the selected notifications and initiates the download.
Filter Notifications by Channel
Given an administrator filters notifications by channel, when they select SMS or App alerts, then the system updates the list to show only notifications sent via the chosen channel.

Error Radar

Continuously scans billing entries in real time to detect common errors such as missing modifiers, invalid codes, or mismatched patient details. Provides instant visual alerts and guided corrections to help managers resolve discrepancies before claim submission, reducing rejections and expediting revenue cycles.

Requirements

Real-Time Billing Error Detection
"As a practice manager, I want billing entries to be scanned in real time so that I can catch and correct errors immediately and avoid claim rejections."
Description

Implement a continuous scanning engine that analyzes billing entries as they are created or modified, identifying common errors such as missing modifiers, invalid CPT/ICD codes, and mismatched patient insurance details. The engine should integrate seamlessly with the Pulseboard dashboard, ensuring that potential claim issues are caught instantly and prior to submission, thereby reducing reimbursement delays and administrative workload.

Acceptance Criteria
Missing Modifier Alert Detection
Given a billing entry is saved without a required modifier, When the Real-Time Billing Error Detection engine scans the entry, Then an alert labeled 'Missing Modifier' is displayed next to the entry within 2 seconds.
Invalid Code Identification
Given a user enters an invalid CPT or ICD code, When the entry is submitted, Then the system highlights the code field in red and provides an error message specifying 'Invalid Code' with a suggested valid code list.
Patient Insurance Mismatch Alert
Given a billing entry’s insurance details do not match the patient record, When the entry is created or updated, Then an 'Insurance Mismatch' alert is triggered and a tooltip displays the mismatched fields.
Dashboard Integration and Alert Display
Given multiple billing errors across different entries, When the user views the Pulseboard dashboard, Then all active error alerts are summarized in an 'Error Radar' panel with clickable indicators that navigate to each erroneous entry.
Real-Time Update Performance
Given any billing entry is modified, When the modification occurs, Then the Real-Time Billing Error Detection engine re-scans and updates error statuses within 3 seconds without requiring a page refresh.
Visual Alert Dashboard
"As a practice manager, I want clear visual alerts on the dashboard so that I can quickly identify where billing errors exist."
Description

Design and integrate real-time visual indicators into the Pulseboard interface that highlight erroneous entries using color-coded icons or badges. Alerts should be context-sensitive, appearing next to the specific field in error and summarizing the issue with a tooltip or pop-over. This ensures quick recognition of problems without disrupting workflow.

Acceptance Criteria
Missing Modifier Entry
Given a billing entry missing a required modifier, When the user attempts to save or navigate away, Then a red exclamation icon appears adjacent to the modifier field; And hovering over the icon displays the tooltip "Modifier is required for this procedure"; And the icon remains until a valid modifier is entered.
Invalid Code Entry
Given a billing entry with an invalid CPT code, When the code is entered or updated, Then a yellow warning badge appears next to the code field; And the badge tooltip reads "Invalid code detected - please verify CPT code"; And the code field border changes to yellow.
Mismatched Patient Detail Alert
Given patient demographic details that do not match insurance records, When the system imports or the user updates details, Then a blue info badge appears next to each field with mismatched data; And hovering over the badge shows the message "Patient detail mismatch - review insurance information"; And the badge persists until details align with records.
Multiple Concurrent Errors
Given multiple errors across different fields in the same billing entry, When the user views the form, Then an error summary badge appears at the top of the section displaying the total error count; And individual field-level error icons remain beside each invalid entry; And hovering over the summary badge lists each error with a link to the field.
High-Volume Real-Time Scanning
Given 100 billing entries submitted in under one minute, When the system scans for errors in real time, Then visual alerts for each error appear within 1 second of entry; And no alerts are missed; And the interface performance overhead remains under 200ms additional latency per entry.
Guided Correction Workflow
"As a practice manager, I want a guided correction tool so that I can efficiently fix billing errors without relying on external references."
Description

Provide an interactive, step-by-step correction assistant that guides users through resolving each detected error. The workflow should suggest valid codes or modifiers, auto-fill patient details when appropriate, and validate corrections in real time. Upon resolution, the assistant confirms that the entry is error-free before allowing claim submission.

Acceptance Criteria
Suggesting Valid Modifiers
Given a billing entry with missing or invalid modifiers, when the user initiates the correction workflow, then the system displays within 2 seconds a list of at least three valid modifier suggestions relevant to the selected procedure code.
Auto-Filling Patient Details
Given a detected mismatch between the billing entry and patient record, when the user opens the correction assistant, then the system auto-populates patient name, date of birth, and insurance ID fields from the existing record, and highlights any fields requiring manual confirmation.
Real-Time Validation Feedback
Given the user applies a suggested correction, when the change is made, then the system validates the updated entry in real time and displays a green checkmark if no errors remain, or new error messages if additional issues are detected.
Sequential Guidance Through Multiple Errors
Given a billing entry with multiple errors, when the user proceeds through the correction workflow, then the system presents errors one at a time in a logical order, requiring resolution of the current error before moving to the next.
Final Confirmation Before Submission
Given that all detected errors are resolved, when the user completes the correction workflow, then the system displays a summary screen confirming 'All errors resolved' and enables the 'Submit Claim' button.
Modifier and Code Validation Rules
"As a billing specialist, I want automated validation of code and modifier combinations so that I ensure compliance with current billing standards."
Description

Develop a comprehensive set of validation rules for common CPT, ICD, and modifier combinations. The system should automatically reference the latest code tables and billing guidelines, rejecting invalid pairings and recommending correct alternatives. Validation logic must be updated regularly to reflect regulatory changes.

Acceptance Criteria
Real-time Entry Validation
Given a user enters a CPT code and modifier into a new billing entry When they submit the entry Then the system flags any invalid code-modifier combination, displays an error message indicating the issue, and presents at least one valid alternative
Bulk Upload Validation
Given a CSV file with multiple billing entries is uploaded When the system processes the file Then each entry is validated against the code tables, invalid pairings are listed with corresponding row numbers, and a summary report of errors and suggested corrections is generated
Scheduled Code Table Synchronization
Given the daily sync schedule arrives When the system connects to the code provider API Then it retrieves the latest CPT, ICD, and modifier tables, updates the internal tables without manual intervention, and logs the update status
Guided Correction Flow
Given an entry fails validation When the user clicks on a flagged error Then the system displays a guided correction panel that highlights the error, offers dropdowns of valid codes or modifiers, and updates the entry upon selection
Audit Trail for Validation Actions
Given any validation event occurs When a code-modifier combination is rejected or corrected Then the system records the event with user ID, timestamp, original values, and corrected values in an audit log accessible in the reports dashboard
Patient Data Consistency Check
"As a practice manager, I want the system to check that patient information is consistent across entries so that I reduce errors due to incorrect or outdated data."
Description

Implement cross-field consistency checks that compare patient demographic and insurance information across multiple entries. The system should flag discrepancies such as mismatched dates of birth, policy numbers, or subscriber details, offering to sync data fields from the most recent verified record.

Acceptance Criteria
Billing Entry Data Entry Consistency
Given a user submits a billing entry with a patient date of birth that differs from the latest verified record, When the entry is saved, Then the system displays a 'Date of Birth Mismatch' alert and prevents claim submission until resolved.
Insurance Policy Number Verification
Given a new billing record contains an insurance policy number that does not match the verified patient record, When the record is processed, Then the system highlights the policy number field in red, provides an option to sync with the verified record, and blocks submission until corrected.
Subscriber Details Cross-Check
Given subscriber name or relationship fields in a billing entry differ from the verified patient insurance details, When the user attempts to finalize the entry, Then the system prompts an alert displaying both sets of details and offers to overwrite with the verified data.
Bulk Patient Record Upload Validation
Given a batch upload of patient records is performed, When the system detects mismatches in date of birth or policy numbers compared to existing verified records, Then the upload logs each discrepancy, generates a report, and prevents import of inconsistent records.
Manual Record Correction Sync
Given a manager manually updates patient demographic or insurance fields, When the update is saved, Then the system compares all related entries, flags discrepancies, and provides a one-click option to propagate the manual update to all inconsistent records.

Smart Code Assist

Utilizes AI-driven analysis of diagnosis notes and procedure descriptions to suggest the most accurate billing codes. Offers one-click insertion and justification rationale, minimizing manual code research, improving coding accuracy, and ensuring maximum reimbursement.

Requirements

AI-Driven Code Suggestion
"As a medical biller, I want AI-driven code suggestions based on my diagnosis entries so that I can reduce coding errors and speed up the billing process."
Description

Implement an AI model that analyzes diagnosis notes and procedure descriptions in real time to suggest the most accurate billing codes. This functionality reduces manual code lookup, speeds up billing workflows, and ensures compliance by leveraging up-to-date coding guidelines. The feature seamlessly integrates with the Pulseboard dashboard, highlighting suggestions next to user-entered notes and allowing effortless review and selection without disrupting the user’s workflow.

Acceptance Criteria
Real-time Billing Code Suggestion
Given a user enters diagnosis notes in the Pulseboard text field When the user pauses typing for 2 seconds Then the AI model displays up to three suggested billing codes ranked by confidence next to the notes And each suggestion includes a confidence score of 85% or higher
One-Click Code Insertion Workflow
Given a list of AI-suggested codes is displayed When the user clicks the “Insert Code” button next to a suggestion Then the selected code is inserted into the billing form field And the form field updates without a full page reload
Justification Rationale Display
Given a billing code suggestion is shown When the user clicks on the info icon beside the suggestion Then a tooltip opens displaying the rationale text of at least 50 words explaining code selection And the rationale references the specific keywords from the diagnosis notes
Fallback for Unsupported Cases
Given the AI model cannot confidently suggest a code (confidence below 60%) When the user submits the notes for suggestion Then the system displays a message “No confident matches found, please review manually” And disables the one-click insertion for that note
Integration with Coding Guidelines Updates
Given the published coding guidelines are updated in the source repository When the system syncs with the repository daily at 2 AM Then the AI model uses the updated guidelines for all code suggestions And a log entry is created confirming the guideline version loaded
One-Click Code Insertion
"As a clinic manager, I want to insert suggested billing codes with a single click so that I can complete billing entries faster and without mistakes."
Description

Provide a one-click mechanism that lets users accept suggested billing codes and insert them directly into the billing record. This requirement focuses on minimizing clicks, eliminating copy-paste errors, and maintaining data integrity. The inserted code is automatically linked to the patient encounter and visible in downstream billing sections, ensuring consistent data flow across the system.

Acceptance Criteria
Inserting Suggested Code into Open Billing Record
Given a suggested billing code is displayed When the user clicks the "Insert Code" button Then the code is added to the current billing record with a single click and appears in the code list within 1 second
Automatic Linking for Completed Patient Encounter
Given a patient encounter is marked complete and a code is inserted Then the code entry is automatically linked to the encounter ID in the backend and the link is visible in the code details view
Error Handling for Network Interruptions During Insertion
Given the user initiates code insertion and network connection is lost When the insertion fails Then an error message "Insertion failed. Please retry." is displayed and the user can retry insertion without reselecting the code
Validation of Code Presence in Downstream Billing Section
Given a code is inserted When the billing summary section is loaded Then the newly inserted code appears in the summary list with the correct code, description, and justification rationale, and the total billing amount reflects the new code fee
Minimizing Clicks in High-Volume Coding Sessions
Given the user is reviewing multiple suggested codes When the user clicks the insert button sequentially Then each code is inserted with only one click and focus automatically moves to the next suggestion without additional confirmations
Justification Rationale Display
"As an auditor, I want to see why a billing code was suggested so that I can verify its accuracy and compliance."
Description

Display a clear, concise rationale for each suggested billing code, outlining the key terms or phrases from the diagnosis notes that triggered the suggestion. This transparency builds user trust in AI recommendations, facilitates quick auditing, and supports compliance reviews. The rationale appears as a tooltip or side panel adjacent to the code suggestion for easy reference.

Acceptance Criteria
Tooltip Rationale Display on Hover
Given a billing code suggestion is shown, when the user hovers over the suggestion, then a tooltip appears adjacent to the code displaying a concise rationale listing the key phrases from the diagnosis notes that triggered the suggestion.
Side Panel Rationale Display on Code Selection
Given the user clicks on a suggested billing code, when the selection is made, then a side panel opens showing the full justification rationale with highlighted source terms and an explanation of the AI’s decision process.
Accurate Justification Content
Given any suggested billing code with displayed rationale, when the underlying diagnosis notes include key trigger phrases, then the rationale must reference the correct phrases verbatim and align with coding guidelines at least 95% of the time.
Rationale Tooltip Dismissal Behavior
Given a rationale tooltip is visible, when the user clicks outside the tooltip area or moves the cursor away, then the tooltip closes within 300 milliseconds without affecting other UI elements.
Accessibility of Rationale Display
Given the tooltip or side panel is displayed, then it must meet WCAG AA standards for color contrast, be navigable via keyboard (including opening, reading, and closing), and provide screen reader support for the rationale text.
Integration with Diagnosis Notes
"As a practitioner, I want the AI to suggest codes dynamically as I update diagnosis notes so that I don’t have to switch between modules or manually request suggestions."
Description

Ensure seamless integration between the AI coding engine and the clinic’s diagnosis note module. As users type or import clinical notes, the system streams text to the AI engine in real time and returns code suggestions without manual triggers. This bidirectional integration maintains context, avoids data duplication, and ensures suggestions reflect the latest note edits.

Acceptance Criteria
Real-Time Note Typing Trigger
Given a clinician is typing a new diagnosis note When the clinician pauses typing for more than 500 milliseconds Then the system streams the current note text to the AI engine and displays billing code suggestions within 2 seconds
Batch Note Import Integration
Given a clinician imports an existing diagnosis note file When the import completes Then the system automatically sends the full text to the AI engine and populates suggested billing codes in the sidebar without manual action
Note Editing Update
Given an existing note with AI-suggested codes is open When the clinician edits or deletes text in the note Then the system re-sends the updated text to the AI engine and refreshes code suggestions to reflect the latest edits within 2 seconds
Context Preservation Across Edits
Given multiple successive edits to a note When each edit is processed Then the AI engine suggestions maintain context from prior content and do not duplicate codes already accepted or rejected by the user
Error Handling and Retry Mechanism
Given a network or AI engine error occurs during streaming When the system detects the error Then it displays a non-blocking error message, retries the transmission up to 3 times, and informs the user if suggestions cannot be retrieved
Continuous Learning Feedback Loop
"As a billing specialist, I want the system to learn from my coding corrections so that it becomes more accurate over time."
Description

Implement a feedback mechanism where users can confirm, modify, or reject suggested codes, feeding these actions back into the AI model to improve future accuracy. Capture user interactions and outcomes for periodic model retraining, ensuring that the suggestions adapt to clinic-specific coding patterns and evolving guidelines.

Acceptance Criteria
User Confirms Suggested Code
Given a billing code suggestion is displayed, when the user clicks "Confirm", then the system logs a positive feedback event with the confirmed code, timestamp, and user ID.
User Modifies Suggested Code
Given a billing code suggestion is displayed, when the user edits the code or justification, then the system captures the original suggestion, user’s modification, and optional reason, and stores them for model retraining.
User Rejects Suggested Code
Given a billing code suggestion is displayed, when the user clicks "Reject", then the system prompts for an optional rejection reason and logs the rejection event with the provided feedback.
Daily Feedback Export for Retraining
Given it is 2:00 AM local time, when the nightly process runs, then all captured feedback events from the previous 24 hours are aggregated, anonymized, and exported to the model retraining dataset without data loss.
Feedback Impact Analytics
Given the user accesses the AI analytics dashboard after retraining, when the dashboard loads, then it displays updated coding accuracy metrics and model performance improvements based on the integrated feedback.

Claim Preflight

Simulates claim submission against payer systems to predict acceptance likelihood and identify potential denials. Generates a confidence score and a detailed report of flagged issues, empowering users to make corrective edits proactively and avoid costly resubmissions.

Requirements

Payer-specific Rule Library
"As a practice manager, I want the system to reference the latest payer-specific claim rules so that I can ensure submissions meet each insurer's unique requirements."
Description

A centralized, regularly updated repository of payer-specific submission rules, enabling the system to validate claims against the correct criteria for each insurer. The library will be version-controlled and allow adding or modifying rules as payers update their guidelines.

Acceptance Criteria
Rule Retrieval for Claim Validation
Given a payer ID exists in the library When the claim preflight process requests submission rules for that payer Then the system returns the latest active rule set within 2 seconds and includes all validation criteria
Adding New Payer-Specific Rules
Given an administrator enters new payer submission rules in the rule editor When the administrator submits the new rules Then the system saves the rules, assigns a sequential version number, and displays a success confirmation
Modifying Existing Payer Rules
Given an existing payer rule is selected for update When the administrator edits the rule and clicks save Then the system archives the previous version, stores the updated rule as the new active version, timestamps the change, and updates the version history
Version Rollback Functionality
Given a user views the version history of a payer’s rules When the user selects an older version and confirms rollback Then the system marks that version as active, archives the current version, and logs the rollback action with user ID and timestamp
Rule Change Audit Trail
Given any rule add, modify, or rollback action occurs When a user accesses the audit log for that payer Then the system displays entries with action type, user ID, timestamp, version numbers before and after, and a description of the change
Preflight Simulation Engine API
"As a practice manager, I want to submit claim data to a preflight API and receive instant validation feedback so that I can correct errors before final submission."
Description

A backend simulation engine accessible via a secure RESTful API that accepts claim data, runs preflight checks against the rule library in real time, and returns validation results. This engine must handle high throughput and ensure response times under two seconds per request.

Acceptance Criteria
Standard Claim Validation
Given a well-formed claim payload, when the client submits it to the Preflight Simulation Engine API, then the API returns a JSON response containing a confidenceScore (0-100), an issues array with codes and descriptions, and a 200 status within 2 seconds.
High Throughput Performance
Under a sustained load of 100 concurrent API requests with valid claim data, at least 95% of responses must complete within 2 seconds, with no more than 1% error rate.
Invalid Claim Data Handling
Given a claim payload missing one or more required fields, when submitted, then the API responds with a 400 status, and a JSON error message listing each missing field.
Authentication and Authorization
Given a request with a valid API token, the API processes the claim; given an invalid or expired token, the API returns a 401 Unauthorized status without processing the claim.
Detailed Report Content
For any claim with flagged issues, the response must include a detailed report object containing at least ruleId, severity (error/warning), fieldName, and human-readable description for each issue.
Detailed Issue Reporting Dashboard
"As a practice manager, I want a detailed report of claim issues categorized by severity so that I can quickly identify and address the most critical problems."
Description

A user interface module that presents identified claim issues in a structured report, categorizing errors and warnings, linking directly to affected fields, and offering filters by severity and issue type for quick triage by the user.

Acceptance Criteria
Viewing Categorized Issues
Given a completed preflight simulation, when the user opens the Detailed Issue Reporting Dashboard, then the dashboard displays all identified issues grouped into 'Errors' and 'Warnings' categories with counts visible for each group.
Filtering by Severity
Given the report contains issues of varying severities, when the user selects 'Critical' from the severity filter, then only issues with severity labelled 'Critical' are displayed in the dashboard.
Filtering by Issue Type
Given multiple issue types are present in the report, when the user selects one or more issue types from the type filter, then the dashboard displays only the issues that match the selected types.
Navigating to Affected Fields
Given an issue entry lists a link to the affected field, when the user clicks the link, then the corresponding field in the claim form view is highlighted and scrolled into view.
Real-time Update on Simulation
Given the user runs a new claim preflight simulation, when the simulation completes, then the Detailed Issue Reporting Dashboard automatically refreshes within 5 seconds to display updated issue data without requiring a manual page reload.
Confidence Score Calculation
"As a practice manager, I want a confidence score indicating the likelihood of claim acceptance so that I can gauge the risk of denial before submitting."
Description

An algorithm that computes a normalized confidence score for each claim submission attempt based on rule pass/fail counts, severity weights, and historical acceptance data. The score should range from 0 to 100 and update instantly as claim fields change.

Acceptance Criteria
Real-Time Score Update on Claim Field Change
Given a user modifies any claim field that affects rule evaluation When the field change is saved Then the confidence score recalculates and displays an updated value within 500ms
Severity Weight Application in Score Calculation
Given a claim triggers multiple rule failures with assigned severity weights When the confidence score is computed Then each failure’s weight reduces the raw score proportionally and the result reflects the weighted sum of rule outcomes
Incorporation of Historical Acceptance Data
Given historical acceptance rates are available for the payer and claim type When the confidence score calculation runs Then the algorithm adjusts the preliminary score by applying the historical acceptance modifier according to the defined formula
Normalization of Raw Score to 0–100 Range
Given a raw score computed from rule outcomes and modifiers When the normalization step executes Then the final confidence score is scaled linearly to a 0–100 range, with minimum and maximum bounds enforced
Perfect Claim with No Rule Failures
Given a claim passes all validation rules with no failures When the confidence score is calculated Then the final score equals 100
In-app Correction Suggestions
"As a practice manager, I want in-editor suggestions for fixing claim errors so that I can correct issues efficiently without searching documentation."
Description

A corrective guidance component integrated into the claim editor that suggests specific field edits or additions to address flagged issues. Suggestions should link to rule definitions and include tooltips explaining required changes, minimizing guesswork and speeding up corrections.

Acceptance Criteria
Suggestion Generation Upon Flagging
Given a claim with flagged issues When the user opens the claim editor Then each flagged issue displays at least one in-app correction suggestion specifying the field name and proposed edit
Tooltip Explanation for Suggestions
Given a displayed correction suggestion When the user hovers over the suggestion indicator Then a tooltip appears explaining why the change is required and referencing the relevant rule definition
Rule Definition Link Functionality
Given a correction suggestion is displayed When the user clicks the rule link in the suggestion Then the system opens the detailed rule definition in a side panel without losing the current claim context
Inline Application of Selected Suggestion
Given one or more correction suggestions are visible When the user selects “Apply” on a suggestion Then the corresponding field in the editor auto-updates with the suggested value
Persistence of Suggestions After Save
Given the user applies one or more suggestions and saves the claim When the editor reloads or the claim is reopened Then only unresolved suggestions remain displayed and applied corrections are removed from the suggestion list

Policy Pulse

Integrates up-to-date payer-specific policies and fee schedules to validate claims against individual insurer rules. Automatically checks for coverage limits, bundling restrictions, and documentation requirements, ensuring each claim aligns with payer guidelines to minimize denials.

Requirements

Payer Policy Data Sync
"As a practice manager, I want policy data to sync automatically so that I always work with the latest insurer rules without manual updates."
Description

Automate the retrieval and integration of the latest payer-specific policies and fee schedules into Pulseboard’s database. This process involves scheduled API calls to insurer endpoints, parsing incoming policy data, and updating local records without manual intervention. The sync ensures the system maintains up-to-date rules on coverage limits, bundling restrictions, and documentation requirements, reducing manual maintenance tasks and improving claim accuracy.

Acceptance Criteria
Scheduled Policy Sync Execution
Given the sync schedule is configured, When the scheduled time arrives, Then the system must send API requests to all configured insurer endpoints within 1 minute and receive a 200 response for each.
Policy Data Parsing Accuracy
Given a valid JSON response from an insurer API, When the data is parsed, Then all policy fields (coverage limits, bundling restrictions, documentation requirements) are extracted and stored in local staging tables matching the payer data schema with zero data loss.
Database Update Integrity
Given parsed policy data in staging tables, When the update process runs, Then the existing payer policy records are upserted in the main database so that the total record count matches the incoming dataset and no duplicate records exist based on payer ID and policy version.
Error Handling and Retry Mechanism
Given an API call failure (non-200 response or network timeout), When the sync process encounters the error, Then the system logs the error, retries up to 3 times at 5-minute intervals, and flags any unresolved endpoints for manual review.
Sync Audit Logging
Given each sync operation, When the sync completes or fails, Then the system logs timestamps, endpoint responses, processed record counts, and final status (success/failure) in the audit log table retrievable by date range.
Coverage Limit Validation
"As a billing specialist, I want claims automatically checked for coverage limits so that I can catch and correct overages before submission."
Description

Implement a validation engine that cross-references each claim line item against payer-defined coverage limits. The engine will flag or block claims exceeding allowable quantities or frequency thresholds, provide real-time feedback on violations, and display suggested adjustments. This reduces denials due to overutilization and improves first-pass claim acceptance rates.

Acceptance Criteria
Exceeding Quantity Threshold Detection
Given a claim line item submitted with a quantity exceeding the payer-defined maximum, when the claim is validated, then the system flags the line item as exceeding the quantity threshold and prevents submission until adjusted.
Frequency Limit Enforcement at Claim Submission
Given multiple claim line items for the same service code within a defined period, when the user attempts to submit the claim, then the validation engine blocks submission if the total frequency exceeds the payer’s limit and displays an error message specifying the violation.
Real-time Feedback Display
Given a user enters or updates a claim line item that breaches a coverage limit, when the data is entered, then the system immediately displays a warning tooltip detailing the rule violated and the allowable limit without requiring manual validation.
Suggested Adjustment Recommendations
Given a flagged claim line item violating coverage limits, when the user views the violation details, then the system provides at least one suggested adjustment (e.g., reducing quantity or splitting claims) that complies with payer policy.
High Volume Claims Batch Validation
Given a batch upload of 100 or more claim line items, when the batch is processed, then the engine validates each line item against coverage limits within 30 seconds, flags violations, and generates a summary report of errors.
Bundling Rule Enforcement
"As a coding technician, I want automatic bundling rule checks so that I can adjust codes correctly and avoid denials for unbundled services."
Description

Develop a bundling rule processor that evaluates service codes within a claim to identify and enforce insurer-specific bundling restrictions. The system will detect incompatible code combinations, suggest appropriate modifiers or alternative codes, and prevent submission of claims with bundling violations. This feature minimizes the risk of denials from unbundled services.

Acceptance Criteria
Incompatible Service Codes Detection
Given a claim containing service codes A123 and B456 which are mutually exclusive for insurer XYZ, when the bundling rule processor evaluates the claim, then it flags a bundling violation, displays an error message naming both codes, and prevents the claim from being submitted.
Modifier Suggestion for Bundled Services
Given a claim with service code C789 that requires a specific modifier when billed with code D012 under insurer ABC rules, when the processor detects the bundled relationship, then it suggests the correct modifier code in a clear recommendation within the user interface.
Alternative Code Recommendation
Given a claim where service code E345 is fully bundled under code F678 for insurer DEF, when the processor evaluates the claim, then it identifies the bundling restriction, suggests an unbundled alternative service code if available, and displays the recommendation to the user.
Batch Claim Processing with Mixed Bundling Rules
Given a batch of 50 claims with various code combinations across multiple payers, when the processor runs in batch mode, then it applies the correct bundling rules to each claim, flags violations individually, and generates a summary report listing each flagged claim and the specific rule violated.
Allowed Code Combination Pass-Through
Given a claim containing service codes G901 and H234 which are allowed together under insurer GHI rules, when the processor evaluates the claim, then it verifies no bundling rule applies, allows submission without error, and marks the claim as compliant.
Documentation Requirements Tracker
"As a claims processor, I want to know which documents are required for each claim so that I can attach them before submitting and prevent incomplete claim denials."
Description

Create a module that associates claims with required documentation criteria specified by each payer. The tracker will prompt users to attach necessary clinical notes, referral forms, or EOBs before claim submission. It will also store documentation status, send reminders for missing items, and ensure compliance with payer-specific record-keeping policies.

Acceptance Criteria
Claim Submission with Complete Documentation
Given a claim has all required clinical notes, referral forms, and EOBs attached, when the user clicks ‘Submit Claim’, then the system allows submission, updates the documentation status to ‘Complete’, and removes any missing‐document prompts.
Claim Submission with Missing Referral Form
Given a claim lacks a required referral form, when the user attempts to submit the claim, then the system blocks the submission, displays an error listing the missing referral form, and highlights the requirement in the tracker.
Automated Reminder Trigger for Missing Clinical Notes
Given a claim has been in draft status for more than 24 hours without clinical notes attached, when the 24‐hour threshold is reached, then the system automatically sends a reminder notification to the assigned user specifying the missing clinical notes.
Historical Documentation Status Retrieval
Given a previously submitted claim, when a user views its details in the tracker, then the system displays a chronological audit trail of documentation status changes with timestamps and user IDs.
Compliance Validation Against Payer Policies
Given payer documentation requirements are updated, when a user opens an existing claim, then the system revalidates attached documents against the new requirements and flags any discrepancies for user action.
Policy Exception Alerting
"As a practice manager, I want to receive alerts about policy exceptions so that I can adjust workflows and avoid claim disruption."
Description

Introduce an alert system that monitors for exceptions or unusual changes in payer policies—such as sudden adjustments to fee schedules or new bundling rules. When detected, the system will notify administrators via in-app messages and email summaries, providing details of the exception and recommendations for next steps. This proactive alerting helps teams respond quickly to policy shifts.

Acceptance Criteria
Detect Sudden Fee Schedule Adjustments
Given the system ingests updated payer policy feeds continuously When a fee schedule change is received that differs by more than 5% from the previous schedule Then an exception alert is generated within 5 minutes and an entry is created in the alert log
Identify New Bundling Restrictions
Given current payer policy definitions When a new bundling rule is added to the payer's fee schedule Then the system flags the policy exception and displays the new rule in the exception details page
Monitor Coverage Limit Modifications
Given defined coverage limits for services When a coverage limit is modified or removed Then an alert is generated and sent via in-app notification and included in the daily email summary
Notify on Documentation Requirements Changes
Given stored documentation requirements for claims When the payer updates or adds documentation requirements Then the system generates an alert containing the new requirements and recommended next steps
Send Administrator Alert on Policy Exception
Given any detected policy exception When the exception is logged Then an in-app notification and an email summary are sent to all administrators within 10 minutes containing the exception details and mitigation recommendations

Batch Shield

Allows managers to upload and scan entire batches of claims at once, providing a consolidated dashboard with pass/fail status, error summaries, and prioritization suggestions. Streamlines high-volume workflows and accelerates the review process for busy billing teams.

Requirements

Bulk Claim Upload
"As a billing manager, I want to upload entire batches of claims at once so that I can reduce manual data entry and speed up the claims submission process."
Description

Allows managers to select and upload multiple insurance claims simultaneously via CSV or EDI file import, with front-end validation to ensure file format compliance and immediate feedback on any upload issues.

Acceptance Criteria
Valid Bulk CSV File Upload
Given a valid CSV file containing multiple claims When the manager uploads the file Then all claims are accepted, processed, and a Pass status is displayed for each claim within 10 seconds
Invalid File Format Rejection
Given a file in a format other than CSV or EDI When the manager attempts to upload Then the system rejects the upload and displays an error message stating "Unsupported file format"
Front-End Format Compliance Validation
Given a CSV file missing required headers When the manager tries to upload Then the front-end highlights the missing headers, disables the upload button, and shows a validation message listing the missing fields
Error Summary and Prioritization Suggestions
Given a batch upload with both valid and invalid claims When processing completes Then the dashboard displays a summary of errors, groups failed claims by error type, and provides prioritization suggestions based on error severity
Large Batch Performance
Given a single file containing 5,000 claims When the manager uploads the file Then the system processes the file and returns a full processing report within 30 seconds
Real-Time Batch Scanning
"As a billing team member, I want the system to scan my uploaded claim batches in real time so that I can identify and address errors without delay."
Description

Implements a backend processing service that scans each batch upload in real time, verifying claim data fields against payer rules and internal policies, and flags any discrepancies instantly.

Acceptance Criteria
Bulk Upload Submission
Given a batch file containing multiple claims is uploaded, when the file is processed, then each claim is scanned in real time and a pass/fail status is returned for all claims within 30 seconds per 100 claims.
Compliance Rule Verification
Given a batch includes claims with missing or incorrect payer codes, when the scanning service runs, then those claims are flagged with specific error messages that correspond to the applicable payer and internal policy codes.
Real-Time Dashboard Update
Given batch scanning is in progress, when any claim status changes, then the dashboard updates the overall pass/fail counts and individual claim statuses within 5 seconds.
Error Prioritization Suggestions
Given multiple claims in a batch are flagged with errors, when scanning completes, then the system provides a prioritized list of the top five errors sorted by frequency and potential revenue impact.
Scalability Under Load
Given a batch upload of 1,000 or more claims, when multiple users trigger scans concurrently, then the processing service completes without failures, maintaining system CPU usage below 70% and meeting the standard SLA.
Error Categorization Dashboard
"As a practice manager, I want to see a categorized list of errors for my batch claims so that I can quickly focus on the most critical issues."
Description

Provides a unified dashboard summarizing pass/fail status of each claim in the batch, categorizing errors by type (e.g., missing information, payer rejections, formatting), and offering drill-down details for each failed claim.

Acceptance Criteria
Viewing Batch Processing Results
Given a processed batch of claims, when the manager opens the Error Categorization Dashboard, then the dashboard displays pass/fail status for each claim in the batch.
Real-time Dashboard Updates
Given a new batch is uploaded, when processing completes, then the dashboard automatically refreshes to show updated pass/fail statuses and error categorizations without manual page reload.
Filtering Errors by Category
Given failed claims are categorized by error type, when the manager selects an error category, then only claims with that error type are displayed in the dashboard.
Drill-down Error Details
Given a failed claim entry on the dashboard, when the manager clicks on the claim, then a detail view opens showing the full error summary and relevant claim data for correction.
Error Prioritization Suggestions
Given multiple error types across claims, when errors are summarized, then the dashboard highlights the top three most frequent error categories and provides suggested corrective actions.
Priority Suggestion Engine
"As a billing specialist, I want automated suggestions on which errors to fix first so that I can maximize revenue recovery and minimize delays."
Description

Analyzes common error patterns and payer impact to automatically suggest a prioritized remediation order, highlighting high-value or time-sensitive claims that should be addressed first.

Acceptance Criteria
High-Value Claim Prioritization
Given a batch containing claims with varying reimbursement amounts, when the batch is processed by the Priority Suggestion Engine, then claims are listed in descending order of expected reimbursement, with the highest-value claims at the top of the priority list.
Deadline-Sensitive Claim Nudging
Given claims in the batch that have submission deadlines within the next 24 hours, when the batch is scanned, then those deadline-sensitive claims are flagged and appear above other claims in the suggested remediation order.
High Denial-Risk Claim Ordering
Given historical payer denial data and error patterns, when the Priority Suggestion Engine analyzes the batch, then claims with the highest calculated denial risk score are prioritized before lower-risk claims.
Mixed Error Batch Sorting
Given a batch of claims containing multiple error types (e.g., missing codes, invalid patient data), when the system generates suggestions, then claims are ordered first by error severity level, then by payer impact, displaying the most severe errors at the top of the dashboard.
Large Batch Performance
Given a batch of more than 1,000 claims uploaded simultaneously, when the Priority Suggestion Engine processes the batch, then the complete prioritized remediation list is generated and displayed within 30 seconds without performance degradation.
Batch Reporting Export
"As a clinic administrator, I want to export batch processing reports so that I can share insights with my team and maintain records."
Description

Enables export of batch scan results to PDF or Excel, including summary statistics, error overviews, and remediation suggestions, for sharing with stakeholders or archiving.

Acceptance Criteria
Stakeholder PDF Report Generation
Given a completed batch scan When the user selects "Export to PDF" Then a PDF file is generated and automatically downloaded And the PDF includes the batch ID, scan date, and user name in the header And the PDF displays all claim scan results without rendering errors
Excel Report Download by Billing Manager
Given a completed batch scan When the user selects "Export to Excel" Then an .xlsx file is generated and automatically downloaded And the Excel file contains separate sheets for summary statistics, error details, and remediation suggestions And the file opens correctly in Microsoft Excel without formatting issues
Summary Statistics Inclusion in Exports
Given the user initiates an export When the export file is generated Then it includes total number of claims, passed claims count, failed claims count, and overall pass rate And the numeric values exactly match those shown on the batch scan dashboard
Error Details and Remediation Export
Given claims with errors in the batch scan When the user exports the results Then the export lists each failed claim number alongside its error code and description And includes a corresponding remediation suggestion for each error type
Export File Naming Convention Compliance
Given the export completes successfully When the file is downloaded Then the filename follows the format "Batch_[BatchID]_[YYYYMMDD_HHMMSS].[pdf|xlsx]" And the timestamp reflects the actual generation time And the file is saved to the user's default download directory

Rejection Insights

Aggregates historical claim rejection data to identify recurring denial patterns and root causes. Delivers interactive analytics and targeted recommendations, enabling billing professionals to address systemic issues and continuously improve claim success rates.

Requirements

Denial Pattern Recognition
"As a billing specialist, I want the system to automatically identify and categorize recurring claim denial patterns so that I can quickly understand where most rejections are occurring and prioritize corrective actions."
Description

Implement an algorithmic engine that processes and aggregates historical claim rejection data to automatically detect recurring denial patterns, categorize them by type (e.g., coding errors, eligibility issues), and surface the most frequent and impactful patterns for further analysis.

Acceptance Criteria
Monthly Denial Pattern Analysis
Given a minimum of six months of historical claim rejection data is available, When the denial pattern recognition engine runs a monthly aggregation, Then the system lists all denial patterns that occur in at least 5% of total monthly rejections with their frequency counts.
Denial Type Categorization
Given aggregated claim rejection data, When the engine processes the data, Then each detected denial pattern is categorized into predefined types (e.g., coding errors, eligibility issues, documentation gaps) with at least 95% classification accuracy.
Top Frequent Denial Codes Detection
Given processed rejection data, When the system identifies recurring denial patterns, Then the top five denial codes by occurrence are displayed in descending order, each accompanied by its occurrence percentage and count.
Impact Score Sorting
Given identified denial patterns with associated financial impact scores, When the user requests sorting by impact, Then the patterns are sorted by descending impact score and the list updates within two seconds.
Export Denial Patterns Report
Given the identified denial patterns on the dashboard, When the user selects export, Then the system generates a CSV report containing pattern ID, description, category, frequency, and impact score and prompts the user to download within five seconds.
Real-Time Pattern Update
Given new claim rejection data is ingested, When real-time processing is triggered, Then the dashboard updates denial pattern metrics within one minute of data ingestion.
Root Cause Drilldown
"As a billing manager, I want to drill down into specific denial patterns to see detailed root cause information so that I can address underlying issues accurately and reduce future rejections."
Description

Provide an interactive interface enabling users to drill down into each identified denial pattern to explore detailed root cause data, including claim fields, provider notes, payer responses, and timeline of events, facilitating deep analysis and targeted resolution.

Acceptance Criteria
Access Denial Pattern Drilldown Interface
Given a user selects a denial pattern from the dashboard, When they click the “Drilldown” icon, Then the system displays the Root Cause Drilldown interface within 2 seconds, showing claim fields, provider notes, payer responses, and event timeline.
Filter Root Cause Data by Field Type
Given the Root Cause Drilldown interface is displayed, When the user applies a filter for a specific claim field type (e.g., diagnosis code), Then only root cause entries matching that field type appear in the results list.
Sort Root Cause Entries by Date
Given multiple root cause entries are visible, When the user selects “Sort by Date” ascending or descending, Then the entries reorder correctly within 1 second to reflect the selected date sort order.
Timeline Event Hover Details
Given the user views the timeline of events for a root cause, When they hover over a timeline marker, Then a tooltip appears displaying event details including timestamp, action taken, and user comments.
Export Detailed Root Cause Report
Given the user has completed analysis on a specific denial pattern, When they click “Export Report” and choose CSV or PDF format, Then the system generates and downloads the report including all drilldown data within 5 seconds.
Recommendation Engine
"As a revenue cycle analyst, I want to receive actionable recommendations based on our claim rejection data so that I can implement proven changes and improve our overall claim acceptance rate."
Description

Develop a recommendation module that leverages analysis of denial patterns and root causes to generate targeted, actionable suggestions—such as coding adjustments, documentation improvements, or payer policy clarifications—with rationale and implementation guidelines.

Acceptance Criteria
Generate Targeted Recommendations Based on Denial Patterns
Given a dataset of historical claim rejections when the recommendation engine analyzes the data then it outputs at least three actionable suggestions each with a clear rationale and detailed implementation guidelines aligned to identified root causes.
Display Recommendations in Interactive Dashboard
Given generated recommendations when a billing professional accesses the Rejection Insights module then the dashboard displays each recommendation with its rationale, implementation steps, and an impact score, allowing sorting and filtering by priority.
User Acceptance and Feedback Logging
Given displayed recommendations when a user accepts or rejects a suggestion then the system logs the user action with timestamp, user identifier, decision rationale, and updates the feedback dashboard for future algorithm refinement.
Performance under High Volume Data
Given a dataset of at least 10,000 claim records when the recommendation engine processes the data then total processing time does not exceed 2 minutes and no errors or timeouts are thrown.
Integration with Payer Policy Updates
Given updated payer policy changes when the recommendation engine regenerates suggestions then the recommendations reflect the latest policy details and cite the specific policy sections influencing each suggestion.
Interactive Analytics Dashboard
"As a practice manager, I want a visual dashboard summarizing denial statistics and trends so that I can monitor performance and communicate insights to stakeholders efficiently."
Description

Design a unified analytics dashboard that visualizes key denial metrics—pattern frequency, rejection rates over time, payer breakdown, and resolution progress—using charts, heatmaps, and trend lines, allowing users to filter, sort, and export data for reporting and decision making.

Acceptance Criteria
Viewing Denial Trends Over Time
Given the user selects the 'Denial Trends' view When the dashboard loads Then a line chart renders showing denial rates over the past 12 months at daily, weekly, and monthly intervals And data is retrieved and displayed within 2 seconds of request And the chart updates in real-time when date range filters are adjusted.
Identifying Top Denial Reasons
Given the user opens the 'Denial Reasons' section When the heatmap is displayed Then the top 5 denial reasons are highlighted by intensity And hovering over each cell shows the reason, count, and percentage And the data reflects filters applied on time period and payer.
Filtering Metrics by Payer
Given the dashboard is visible When the user selects one or more payer filters Then all charts and tables update to only show data for those payers And the filter selection is visually indicated And clearing the filter resets views to include all payers.
Tracking Claim Resolution Progress
Given the user navigates to 'Resolution Progress' When the progress bar view loads Then it displays counts of claims in pending, in-review, and resolved states And color codes each state distinctly And clicking on a state drills down to detailed claim lists.
Exporting Analytics for Reporting
Given the dashboard data is filtered When the user clicks 'Export to CSV' Then a CSV file downloads containing all visible metrics and filters applied And the file name includes the date range and payer filter names And the CSV columns match the order and labels shown on the dashboard.
Real-time Notification Alerts
"As a billing coordinator, I want to receive immediate alerts when a denial pattern spikes beyond a defined threshold so that I can investigate and address significant issues before they impact revenue."
Description

Implement a notification system that alerts users in real time when new or escalating denial patterns exceed configurable thresholds, delivering in-app messages, email summaries, or SMS to ensure timely awareness and response to critical billing issues.

Acceptance Criteria
New Denial Pattern Exceeds Threshold
Given a new denial pattern occurs 6 times within 10 minutes and the configured threshold is 5 When the system processes incoming claim data in real time Then an in-app notification is displayed within 5 seconds And an email alert is sent to the user's registered address within 1 minute
Escalating Denial Pattern Detected
Given an existing denial pattern increases by more than 20% compared to the previous hour When the pattern escalation is identified Then an in-app notification is generated with escalation details And an SMS is sent to the on-call billing specialist within 2 minutes
User Receives SMS Notification
Given a user has enabled SMS alerts in their notification settings When a critical denial pattern threshold is exceeded Then an SMS message is delivered to the user's verified phone number within 2 minutes And delivery receipt is logged in the notification history
Daily Email Summary Dispatch
Given it is 6:00 PM local time When there have been any notification events during the day Then a consolidated email summary of all alerts is sent to the user And the email includes a breakdown by pattern type and time of occurrence
Notification Delivery Failure Handling
Given the system fails to deliver an email or SMS notification When a delivery error is detected Then the system retries delivery up to 3 times at 5-minute intervals And logs the failure and retry attempts And sends an in-app alert to notify the user of the delivery issue

Scenario Simulator

Immerses new hires in realistic scheduling and billing scenarios through interactive simulations. By practicing common tasks and troubleshooting in a risk-free environment, users build confidence and competence before handling real clinic operations.

Requirements

Interactive Scenario Builder
"As a new practice manager, I want to create and customize training scenarios so that I can practice specific clinic scheduling and billing workflows relevant to my practice."
Description

Allows administrators to design and configure training scenarios with customizable scheduling and billing events, including patient arrivals, appointment changes, insurance verification, and branching conditions. The builder features a drag-and-drop interface for creating realistic clinic workflows, parameter settings for variables such as appointment types and billing codes, and seamless integration into the Pulseboard dashboard for immediate simulation. This empowers new hires to practice tailored scenarios that reflect their clinic’s unique processes.

Acceptance Criteria
Designing a New Clinic Workflow
Given an administrator is in the Interactive Scenario Builder, when they drag and drop at least one scheduling event and one billing event onto the canvas and save the scenario, then the system persists the workflow configuration and lists the new scenario in the scenarios library within 3 seconds.
Customizing Appointment Types
Given an administrator selects an appointment event, when they adjust its type, duration, and parameters (e.g., patient class, resource allocation) and apply changes, then the event properties panel reflects the updated values and the preview simulation updates accordingly.
Configuring Insurance Verification Steps
Given an administrator includes an insurance verification event, when they define required fields (insurance provider, coverage details) and set pass/fail branching conditions, then the scenario builder enforces mandatory field validation and shows visual cues for conditional paths.
Adding Branching for No-Show Handling
Given an administrator adds a branching condition for appointment no-shows, when they specify the no-show threshold and subsequent billing action, then the scenario correctly generates alternate workflow paths in the simulation with conditional branching indicators.
Validating Billing Code Integration
Given an administrator inserts billing code events, when they enter valid and invalid billing codes, then the builder flags invalid codes with error messages and accepts valid codes, ensuring integration with the billing code database lookup.
Real-time Feedback Engine
"As a trainee, I want to receive instant feedback during simulations so that I can understand and correct my errors in real time."
Description

Provides instantaneous feedback during simulation exercises by detecting errors in scheduling entries, billing codes, and workflow decisions. The engine highlights mistakes, explains the correct procedures, and suggests next steps in a contextual panel. Integrated with the scoring system, it tracks corrections and adapts feedback based on user performance to reinforce learning objectives.

Acceptance Criteria
Scheduling Entry Validation
Given the user enters an appointment outside clinic hours, when they submit the entry, then the system displays an error message highlighting the invalid time, explains the business hours rule, and suggests the next available valid time slot.
Billing Code Error Detection
Given the user applies a billing code that does not match the selected service, when they proceed to finalize billing, then the engine highlights the code field in red, provides a list of correct billing code suggestions, and links to the code reference guide.
Workflow Decision Feedback
Given the user chooses to complete patient check-in before updating medical records, when the decision is recorded, then the feedback engine prompts that record updates should precede check-in, provides the rationale, and offers a one-click option to reorder tasks.
Adaptive Feedback for Repeated Errors
Given the user repeats the same scheduling error twice within a session, when the second error is detected, then the system escalates feedback by presenting a detailed tutorial popup for that error type and unlocks a dedicated practice mode for targeted correction.
Scoring System Integration
Given the user corrects an error after receiving feedback, when the correction is saved, then the system logs the action in the scoring module, updates the user’s score in real time, and refreshes the performance summary panel to reflect the change.
Branching Logic and Outcome Tracking
"As a user, I want the simulator to adapt scenarios based on my decisions so that I can learn from varied outcomes and understand cause-effect relationships."
Description

Implements dynamic branching logic within scenarios, altering subsequent events and outcomes based on user actions (e.g., no-show appointments, insurance denials). Each decision path is tracked and logged, enabling varied learning experiences and realistic cause-and-effect exploration. Outcome tracking records user choices and results for review and analytics.

Acceptance Criteria
No-Show Appointment Flow
Given a user marks an appointment as no-show, When the simulator applies branching logic, Then a follow-up appointment prompt is displayed and the no-show event is recorded in the outcome log.
Insurance Denial Handling
Given an insurance claim submission, When the system returns a denial code, Then the simulator branches to a denial resolution path, displays denial reasons, and logs the decision outcome.
Decision Path Analytics Logging
Given any user decision within a scenario, When an action is completed, Then the decision path is saved with timestamps, action details, and resulting branch in the analytics database.
Real-Time Branch Transitions
Given a user choice that triggers a branch, When the choice is made, Then the simulator immediately transitions to the appropriate next event without delays and updates the UI accordingly.
Outcome Data Export
Given completed scenario sessions, When an admin exports session data, Then all recorded decisions, timestamps, and outcomes are included in a downloadable report in CSV format.
Contextual Hint Overlays
"As a learner, I want optional hints during simulations so that I can get assistance when I’m unsure without hindering my confidence."
Description

Offers on-demand, context-sensitive hints embedded directly into the simulation interface. Users can reveal guidance for tasks such as entering billing codes or resolving scheduling conflicts. Hints are tiered by difficulty level and can be enabled or disabled by administrators to tailor challenge levels for different training stages.

Acceptance Criteria
Beginner Billing Code Entry Hint Display
Given a beginner user is in the billing code entry task When they click the hint icon Then a context-sensitive overlay appears showing tier 1 guidance with code definitions and examples And the overlay closes when the user clicks outside or selects “Dismiss”
Intermediate Billing Code Entry Hint Display
Given an intermediate user is in the billing code entry task When they click the hint icon Then a context-sensitive overlay appears showing tier 2 guidance with advanced troubleshooting tips And the overlay adjusts based on user progress in the simulation
Scheduling Conflict Resolution Hint Display
Given a user encounters an overlapping appointment conflict in the scheduler When they click the hint icon Then a context-sensitive overlay appears offering step-by-step resolution suggestions And the system prevents saving the schedule until the conflict is resolved
Administrator Hint Level Configuration
Given an administrator is on the simulation settings page When they select or deselect hint difficulty tiers Then the system saves the configuration and applies the selected tiers to all future user sessions
Hint Disable Functionality for Assessment Mode
Given the simulation is switched to assessment mode When a user attempts to click the hint icon Then the hint icon is hidden or disabled And no hint overlays can be accessed until the mode is switched back
Performance Reporting Dashboard
"As a manager, I want to view comprehensive performance reports so that I can assess trainee progress and identify areas needing improvement."
Description

Generates comprehensive reports on trainee performance across all simulation scenarios, including metrics like task completion time, accuracy of scheduling entries, billing code errors, and feedback resolution rates. Reports are visualized in charts and tables, exportable to PDF or CSV, and integrated with user profiles for ongoing progress tracking and manager review.

Acceptance Criteria
Daily Performance Summary Generation
Given a manager selects a date range and a trainee from the dashboard, when they generate the daily performance report, then the system displays metrics including task completion time, accuracy rate, and feedback resolution rate for that trainee within the selected range.
Comprehensive Report Export to PDF
Given the performance report is generated, when the manager clicks the 'Export to PDF' button, then the system exports a PDF file containing charts and tables matching the on-screen report with correct data formatting and a filename with the trainee's name and date range.
CSV Export of Billing Code Error Data
Given a performance report includes billing code errors, when the manager selects 'Export to CSV', then the downloaded CSV file includes columns for scenario ID, error code, description, date and trainee ID, with all records accurately represented.
Integration with User Profile Progress Tracking
Given a trainee completes a simulation scenario, when the scenario report is generated, then the performance metrics are automatically linked and updated in the trainee's profile under 'Progress Reports' with timestamp.
Historical Performance Data Visualization
Given the manager selects multiple simulations over time, when viewing the performance dashboard, then the system displays interactive charts showing trends in task completion time and accuracy across the selected simulations.

Checkpoint Challenges

Integrates short, gamified quizzes and tasks at critical learning milestones. These interactive checkpoints reinforce knowledge retention, motivate progress, and ensure new hires have mastered essential skills before moving on.

Requirements

Dynamic Checkpoint Triggering
"As a practice manager, I want the system to automatically prompt new hires with targeted quizzes after each training module so that they can reinforce learning immediately and demonstrate competency before proceeding."
Description

The system automatically triggers short, interactive quizzes at predefined training milestones, such as after completing scheduling, billing, or patient flow modules. By integrating with the LMS progress tracker, the feature ensures new hires receive timely reinforcement of key concepts. Real-time notifications prompt users to complete checkpoints, promoting continuous engagement and preventing knowledge gaps.

Acceptance Criteria
Milestone Completion Trigger
Given the user completes a training module and the LMS marks it as 100% complete, when the LMS progress tracker updates, then the system automatically triggers the corresponding checkpoint quiz within 5 seconds.
Scoring and Feedback Delivery
When the checkpoint quiz is launched and the user submits answers, then the system records the score and displays immediate feedback highlighting correct and incorrect responses.
Notification Prompt Accuracy
Given the system triggers a checkpoint quiz, when the quiz becomes available, then the user receives a real-time notification on the Pulseboard dashboard within 3 seconds, and clicking the notification opens the quiz interface.
LMS Integration Sync
When a user attempts or completes the checkpoint quiz, then the system synchronizes the quiz attempt and results with the LMS progress tracker within 10 seconds, ensuring the LMS reflects the user's checkpoint status accurately.
Progression Blocking Enforcement
Given the user has not achieved the minimum passing score of 80% on the checkpoint quiz, then the system prevents progression to the next training module until the checkpoint is passed.
Custom Quiz Builder
"As a practice manager, I want to create and customize checkpoint quizzes so that I can tailor assessments to our clinic’s specific protocols and knowledge requirements."
Description

Provide a drag-and-drop interface for managers to design and customize checkpoint quizzes, including multiple-choice, true/false, and drag-and-match question types. The builder supports question banks, multimedia attachments, time limits, and randomized question order. Integrates seamlessly with Pulseboard’s training modules for consistent branding and user experience.

Acceptance Criteria
Creating a New Quiz via Drag-and-Drop Interface
Given the manager opens the Custom Quiz Builder, when they drag a multiple-choice or true/false question onto the canvas, then the question appears in the correct position; when they drag to reorder questions, then the new order is saved and reflected in the live preview; and the Save button remains disabled until at least one question is added.
Importing Questions from the Question Bank
Given the manager selects the question bank tab, when they choose multiple questions and click Import, then those questions are added to the current quiz without duplicates; and the system displays a confirmation message with the number of questions imported.
Adding Multimedia Attachments to Quiz Questions
Given the manager is editing a question, when they click the Attach Media button and upload an image or video file under 5MB, then the file displays correctly in the question preview; and uploading unsupported file types or oversized files triggers a clear error message.
Configuring Time Limits and Randomization
Given the manager accesses the quiz settings panel, when they set a time limit per question or for the entire quiz, then the timer starts correctly during preview; when they enable randomization, then question order is randomized for each attempt; and disabling these options reverts to default settings.
Previewing and Publishing the Quiz
Given the quiz contains at least one question, when the manager clicks Preview, then the quiz launches in user view with all functionalities (timers, multimedia, randomized order) working; and when the manager clicks Publish, then the quiz is stored in the training module with consistent branding and is available for assignment.
Badge and Leaderboard System
"As a new hire, I want to earn badges and see my rank on a leaderboard so that I feel motivated and recognized for completing checkpoint challenges effectively."
Description

Implement gamification elements by awarding digital badges and ranking users on a leaderboard based on quiz performance, completion time, and consistency. Badges unlock as users master checkpoint challenges, and leaderboards foster healthy competition among new hires. Administrators can view and export leaderboard data for performance reviews.

Acceptance Criteria
Badge Awarding upon Quiz Completion
Given a user completes a checkpoint challenge with a score of 80% or higher, when the final answer is submitted, then the system awards the corresponding badge to the user’s profile within 5 seconds.
Leaderboard Update after Task Completion
Given a user finishes a checkpoint challenge, when the results are processed, then the leaderboard updates in real-time to reflect the user’s new score, completion time, and ranking.
Badge Unlock Notification Display
Given a badge is unlocked, when the badge is added to the user’s profile, then a notification appears on the user’s dashboard within 3 seconds displaying the badge name and description.
Administrator Export of Leaderboard Data
Given an administrator accesses the leaderboard export feature, when they select a date range and click 'Export', then the system generates and initiates download of a CSV file containing user names, badges earned, scores, times, and dates within 10 seconds.
Consistency Tracking over Multiple Challenges
Given a user completes at least five checkpoint challenges in a week, when each challenge is finished, then the system calculates and displays a weekly consistency score on the user’s profile and updates it daily.
Progress Analytics Dashboard
"As a practice manager, I want to view detailed analytics on checkpoint quiz performance so that I can identify knowledge gaps and adjust training accordingly."
Description

Build an analytics dashboard summarizing checkpoint challenge metrics, such as average scores, completion rates, and time taken per quiz. Provides filters by date range, user role, and quiz type. Data visualizations (charts, heatmaps) highlight areas where new hires struggle, enabling targeted training interventions and continuous improvement.

Acceptance Criteria
Filtering by Date Range
Given an admin on the Progress Analytics Dashboard, when they select a valid start and end date and click 'Apply Filters', then the dashboard displays metrics only for quizzes taken within that date range.
Visualizing Average Scores
Given the dashboard is loaded, then an interactive line chart displays average scores per quiz type over the selected time period, with tooltips showing exact values on hover.
User Role Filter Interaction
Given an admin filters by user role, when they select one or more roles and apply the filter, then the completion rates, average scores, and time taken metrics update to reflect only the selected user roles.
Quiz Completion Time Analysis
Given the admin selects the 'Time Taken' view, then a bar chart shows the average time taken per quiz, sortable by quiz type and dynamically updating with other applied filters.
Heatmap Generation for Struggle Areas
Given the dashboard is viewed, then a heatmap highlights quiz questions with the highest failure rates, with color intensity proportional to failure frequency and includes a legend explaining the color scale.
Adaptive Difficulty Algorithm
"As a new hire, I want the quiz difficulty to adjust to my performance so that I’m challenged at the right level and can reinforce areas where I need improvement."
Description

Develop an adaptive algorithm that adjusts checkpoint quiz difficulty in real time based on user performance. The system increases question complexity after consecutive correct answers and revisits foundational questions when errors occur, ensuring personalized learning pacing and optimized knowledge retention.

Acceptance Criteria
Increasing Complexity After Consecutive Correct Answers
Given a user answers three questions correctly in a row, when the next question loads, then the question’s difficulty is increased by one level within the same topic.
Reinforcing Foundational Questions After Incorrect Answers
Given a user answers a question incorrectly, when the next question loads, then the question is selected from the foundational-level pool for that topic until the user answers two foundational questions correctly.
Real-Time Difficulty Adjustment Notification
Given a difficulty level change occurs, when the next question appears, then a difficulty indicator and brief explanation of the change are displayed to the user.
Session Resumption Difficulty Calibration
Given a user resumes a checkpoint after a break, when the session restarts, then the difficulty level is set to the last successfully answered question’s level.
Performance Data Persistence
Given the checkpoint session ends, when data is saved, then the system stores user performance including difficulty progression and timestamps and makes it available in the analytics dashboard within five seconds.

Progress Dashboard

Provides a centralized view of individual training milestones, module completions, and performance analytics. Managers and trainees can track learning progress at a glance, identify areas needing attention, and celebrate achievements.

Requirements

Milestone Progress Visualization
"As a practice manager, I want to view a clear timeline of trainee milestones so that I can monitor progress at a glance and address any delays promptly."
Description

Implement a visual timeline displaying each trainee’s defined training milestones alongside real-time completion status. This feature renders interactive progress bars for individual milestones, highlights upcoming targets, and integrates seamlessly with the training module database. It enables managers to quickly assess where learners stand in their training journey, pinpoint delays, and celebrate achievements, fostering accountability and motivation.

Acceptance Criteria
Trainee Review of Personal Milestone Timeline
Given a trainee is logged in and on the Progress Dashboard When they view their Milestone Progress Visualization Then all assigned training milestones are displayed in chronological order with interactive progress bars And each progress bar correctly reflects the real-time completion percentage from the training module database And completed, in-progress, and upcoming milestones are visually distinguished with distinct colors
Manager Assessment of Team Progress
Given a manager selects a trainee from the team list When they access the Milestone Progress Visualization Then the selected trainee’s timeline is displayed with accurate completion data And any milestone not updated within 7 days is flagged in red And the manager can toggle between individual and aggregated team views
Interactive Drill-Down on Milestone Details
Given a user clicks on a specific milestone in the timeline When the milestone detail pane opens Then it displays the milestone name, assigned date, completion date (if completed), and remaining tasks And the data matches entries in the training module database without latency over 2 seconds
Highlighting Upcoming Training Targets
Given milestones are due within 3 days When the user views the timeline Then those upcoming milestones are automatically highlighted in a distinct color And a tooltip on hover shows the due date and pending tasks
Seamless Data Sync with Training Module Database
Given changes occur in the training module database When a milestone’s status is updated (completed or new assignment) Then the progress visualization reflects the change within 5 seconds And no data discrepancies are reported during repeated refreshes
Module Completion Indicators
"As a trainee, I want to see which modules I’ve completed and which are pending so that I can focus my study efforts efficiently."
Description

Develop status indicators for each training module that reflect completion, in-progress, or not-started states. These indicators pull real-time data from the learning management system and display color-coded badges next to module names. By presenting precise completion data, managers and trainees can immediately identify outstanding modules and track overall curriculum coverage.

Acceptance Criteria
Displaying Module Status on Dashboard
Given the LMS contains modules with statuses 'completed', 'in-progress', or 'not started', when the Progress Dashboard loads, then each module is displayed with a badge colored green for completed, yellow for in-progress, and gray for not started within 2 seconds.
Real-Time Status Synchronization
Given a trainee completes or resumes a module in the LMS, when the dashboard refreshes or the trainee navigates to the Progress Dashboard, then the module’s badge state updates to reflect the new status within 5 seconds without a full page reload.
Module Status Tooltip Details
Given a user hovers or focuses on a module’s status badge, when the tooltip appears, then it displays the exact timestamp of the last status change and the percentage of module completion.
Bulk Module Status Refresh
Given a manager clicks the 'Refresh All' button on the Progress Dashboard, when the action is confirmed, then all module badges update to their current LMS status within 3 seconds, and a success notification appears.
Error Handling for Missing Data
Given the LMS fails to return status for one or more modules, when the dashboard attempts to display those modules, then their badges default to 'unknown' state with a gray outline and a warning icon, and an error message is logged.
Accessibility for Color-Coded Badges
Given a user with color vision deficiency views the dashboard, when using screen reader or high-contrast mode, then each badge includes an accessible label indicating 'completed', 'in-progress', or 'not started' and meets WCAG AA contrast ratios.
Performance Analytics Charts
"As a practice manager, I want graphical reports on training performance so that I can identify trends and areas for improvement."
Description

Create dynamic charts and graphs illustrating metrics such as average completion time per module, pass/fail rates, and individual performance trends. These visual analytics leverage historical and current data, allowing users to filter by trainee, time period, or module. The integration with the analytics engine ensures up-to-date insights, helping managers make data-driven decisions to optimize training programs.

Acceptance Criteria
Filter Charts by Trainee
Given the manager is on the Performance Analytics dashboard, When the manager selects a trainee from the trainee dropdown, Then all charts refresh to display metrics only for that trainee within 2 seconds.
Display Average Completion Time
Given the manager is viewing the dashboard, When the manager sets the time period to the last 30 days, Then the average completion time per module chart displays data points for each module, with values matching backend calculations within a 1% margin of error.
Present Pass/Fail Rates
Given the manager is viewing a module's analytics, When the manager selects pass/fail rate metrics, Then the pass/fail chart shows correct percentages for passed and failed attempts, totaling 100%, based on current and historical data.
Show Individual Performance Trends
Given the manager is viewing an individual trainee's performance, When the manager toggles to performance trends, Then the trend line graph plots completion time and scores over time, correctly reflecting all sessions within the selected date range.
Apply Time Period Filter
Given the manager is on the analytics dashboard, When the manager applies a custom date range filter, Then all charts update to reflect metrics only within that range and display a 'No data available' message if no records exist.
Custom Alerts & Notifications
"As a practice manager, I want to receive alerts when a trainee is falling behind so that I can intervene early and offer support."
Description

Implement a alerts system that notifies managers and trainees when milestones are overdue, performance drops below thresholds, or new modules become available. Notifications can be configured per user and delivered via email or in-app messages. This proactive feature ensures timely interventions, keeps trainees on track, and reduces manual monitoring efforts.

Acceptance Criteria
Overdue Milestone Alert Trigger
Given a milestone is overdue by more than 7 days When the daily scheduled job runs at 08:00 Then an email and in-app notification for the overdue milestone is delivered to the assigned manager within 5 minutes
Performance Threshold Drop Notification
Given a trainee’s performance score falls below the configured threshold When the performance monitoring service detects the drop Then an immediate in-app notification is sent to both the trainee and their manager
New Module Availability Notification
Given a new training module is published in the system When the module status changes to 'Available' Then all users subscribed to new module alerts receive an email and in-app notification within 10 minutes
Notification Preference Update Handling
Given a user updates their notification preferences When the user saves their settings Then the system persists the new preferences and applies them to all subsequent notifications
Email Unsubscribe Fallback
Given a user has unsubscribed from email notifications When the system attempts to send an email alert Then no email is sent and an in-app notification is generated as a fallback
Progress Report Export
"As a practice manager, I want to export comprehensive progress reports so that I can share performance summaries with stakeholders."
Description

Enable users to export detailed training progress reports in PDF and CSV formats. Reports include milestone statuses, module completion data, analytics charts, and custom annotations. The export function integrates with the reporting service, allowing scheduled or on-demand report generation. This capability supports record-keeping, compliance audits, and stakeholder reviews.

Acceptance Criteria
Export Training Progress as PDF on Demand
Given a user is viewing the Progress Dashboard, when the user selects “Export” and chooses “PDF” and clicks “Download,” then a PDF file containing milestone statuses, module completion data, analytics charts, and custom annotations is generated and the download starts within 5 seconds.
Schedule CSV Progress Report via Reporting Service
Given a user configures a report schedule with frequency options (daily, weekly, monthly), when the user saves the schedule, then the reporting service triggers CSV report generation at the configured intervals and sends an email notification with the CSV file attached or a download link.
Include Custom Annotations in Exports
Given a user has added custom annotations to the progress report, when the user exports in PDF or CSV formats, then all annotations appear correctly in the exported document at the user-specified positions.
Validate Analytics Charts Rendering in PDF Export
Given analytics charts are displayed on the Progress Dashboard, when exporting to PDF, then all charts are rendered as high-resolution images matching on-screen data and are fully legible.
Error Handling for Export Failures
Given the reporting service is unavailable or an error occurs during export, when the user initiates an export, then the system displays a clear error message with guidance, logs the error in the audit trail, and prevents partial or corrupt file downloads.

Shadow Scheduler

Enables new hires to schedule live shadowing sessions with experienced staff directly within the training platform. This feature ensures hands-on learning opportunities, personalized mentorship, and smooth integration into team workflows.

Requirements

Mentor Availability Management
"As a mentor, I want to set and update my available times for shadow sessions so that new hires can schedule within my availability without causing conflicts."
Description

Allow experienced staff to define and publish their available time slots for shadowing sessions. The system should integrate with existing clinic schedules to prevent conflicts, enable mentors to block or open slots dynamically, and ensure accurate, up-to-date availability is always shown to new hires.

Acceptance Criteria
Defining Mentor Availability Slots
Given a mentor is on the Mentor Availability Management page and selects a date and time within clinic operating hours, When the mentor confirms the slot, Then the slot is added to their published availability and is immediately visible to new hires.
Preventing Scheduling Conflicts
Given the mentor’s selected time slot overlaps with an existing clinic appointment or blocked period, When the mentor attempts to publish the slot, Then the system rejects the slot and displays a conflict warning.
Dynamic Availability Updates
Given a mentor decides to block a previously published time slot, When they mark that slot as unavailable, Then the slot is removed from published availability in real time and is no longer viewable by new hires.
Real-Time Availability Display
Given a new hire accesses the Shadow Scheduler dashboard, When the new hire refreshes or opens the availability view, Then only currently published, non-conflicting slots are listed and reflect the latest mentor availability.
Automatic Conflict Resolution with Clinic Schedule
Given a new clinic appointment is scheduled that overlaps a published mentorship slot, When the appointment is confirmed, Then the system automatically removes or marks the conflicting mentorship slot as unavailable and notifies the mentor of the change.
Session Booking Interface
"As a new hire, I want to schedule shadowing sessions with a mentor directly in the platform so that I can organize hands-on learning without leaving the training environment."
Description

Provide a seamless, interactive calendar-based interface within the training platform that allows new hires to view mentor availabilities, book, reschedule, or cancel shadow sessions. The UI should be intuitive, mobile-responsive, and reflect real-time changes to mentor schedules.

Acceptance Criteria
New Hire Books a Shadow Session
Given the new hire accesses the calendar on desktop, When they click on an available mentor slot, Then the slot is reserved, a confirmation message is displayed, and the session appears in the new hire's upcoming sessions list.
New Hire Reschedules a Shadow Session
Given the new hire has an existing session, When they select the session and choose a new available slot, Then the original session is removed, the new session is scheduled, and both mentor and new hire receive updated confirmation notifications.
New Hire Cancels a Shadow Session
Given the new hire has a booked session, When they click cancel and confirm the action, Then the session is removed from their schedule, availability is released back to the mentor, and a cancellation confirmation is displayed.
Real-Time Mentor Availability Updates
Given a mentor’s availability changes, When the mentor updates their schedule, Then the new availability is reflected instantly on all active calendar views without page reload.
Mobile Responsiveness of Calendar Interface
Given a new hire accesses the scheduler on a mobile device, When they interact with the calendar, Then all functionality (viewing, booking, rescheduling, cancelling) works correctly, and UI elements adapt to screen size without overlap or truncation.
Notification and Reminders
"As a new hire, I want to receive reminders about upcoming shadow sessions so that I don't miss my scheduled training opportunities."
Description

Implement automated notifications via email, in-app alerts, and push messages to both mentors and mentees for session bookings, cancellations, and upcoming reminders. Users should be able to customize notification preferences and receive timely alerts to minimize no-shows.

Acceptance Criteria
Session Booking Confirmation
Given a mentee completes booking a shadow session, When the booking is confirmed by the system, Then both mentor and mentee receive an email, an in-app alert, and a push notification within 1 minute.
Session Cancellation Alert
Given a scheduled session is canceled by either mentor or mentee, When the cancellation is processed, Then the other party receives an email, an in-app alert, and a push notification immediately.
Upcoming Session Reminder
Given a session is scheduled 24 hours in advance, When the reminder window opens, Then the system sends a reminder notification via the user’s preferred channels (email, in-app, push) exactly 24 hours before the session time.
Notification Preferences Customization
Given a user accesses notification settings, When they enable or disable email, in-app, or push notifications, Then the system saves the preferences and only sends notifications via the selected channels.
Notification Delivery Reliability
Given the system sends notifications, When delivery is attempted, Then at least 95% of notifications are successfully delivered to users’ devices within 2 minutes of the trigger event.
Session Feedback Collection
"As a practice manager, I want to collect feedback on shadow sessions so that I can assess training effectiveness and identify areas for improvement."
Description

After each shadow session, prompt both mentors and new hires to submit feedback through a structured form. Collect ratings, comments, and improvement suggestions. Store feedback centrally to track training quality and mentor performance over time.

Acceptance Criteria
Immediate Feedback Prompt
Given a shadow session concludes, when the session end time is reached, then the system displays a feedback prompt to both the mentor and new hire within 5 seconds.
Structured Feedback Form Accessibility
Given a user clicks on the feedback prompt, when the feedback form loads, then the form displays rating scales for key competencies and a comments field, and all fields are editable.
Feedback Submission Validation
Given a user attempts to submit the feedback form, when required fields are empty, then the system prevents submission and highlights missing fields with error messages.
Centralized Feedback Storage
Given feedback is submitted, when the submission is successful, then the feedback is saved to the central database and is retrievable via the training analytics dashboard.
Feedback Reminder Notification
Given feedback has not been submitted within 24 hours of session end, when the 24-hour threshold is reached, then the system sends an automated email reminder to both mentor and new hire.
Reporting and Analytics Dashboard
"As a practice manager, I want to view reports on shadow sessions so that I can monitor training progress and identify bottlenecks in onboarding."
Description

Build a dashboard that aggregates shadow session data, including number of sessions per mentor, average feedback scores, completion rates, and scheduling trends. Enable filtering by date range, mentor, and new hire cohort to support data-driven training decisions.

Acceptance Criteria
Aggregate Shadow Session Metrics Overview
Given the user opens the Reporting and Analytics Dashboard, the system must display the total number of shadow sessions per mentor, the average feedback score, the session completion rate percentage, and a summary of scheduling trends, accurately reflecting data from all recorded sessions.
Filter Shadow Sessions by Date Range
Given the user sets a valid start and end date, when the filter is applied, then the dashboard must update all metrics and visualizations to include only shadow sessions occurring within the selected date range.
Filter Shadow Sessions by Mentor
Given the user selects one or more mentors from the mentor filter dropdown, when the filter is applied, then the dashboard must update to show metrics and charts exclusively for sessions led by the selected mentors.
Filter Shadow Sessions by New Hire Cohort
Given the user selects a new hire cohort from the cohort filter, when the filter is applied, then the dashboard must update to show metrics and visualizations only for sessions involving new hires in the chosen cohort.
Visualize Scheduling Trends Over Time
Given the user views the scheduling trends section, then the system must render an interactive line chart showing the number of sessions grouped by day or week over the selected date range, with data points matching the underlying session records.
Export Report with Applied Filters
Given the user clicks the ‘Export’ button, when filters are active, then the system must generate and download a CSV file containing all displayed metrics and raw data rows, matching exactly the current dashboard view.

Virtual Coach Chat

Offers an AI-driven in-app assistant that answers questions, provides guidance, and suggests best practices during training. The virtual coach ensures continuous support, reduces downtime, and accelerates problem-solving.

Requirements

Instant Query Response
"As a small practice manager in training, I want the virtual coach to answer my questions instantly so that I can continue learning without interruptions."
Description

Process user queries and generate AI-driven responses within 2 seconds to ensure smooth interaction and minimize downtime. Leverage natural language processing to understand inputs and deliver accurate answers. Integrate with the training module to provide immediate clarification on any feature or workflow, enhancing user confidence and reducing frustration during learning.

Acceptance Criteria
Quick AI Response During Training
Given a user submits a query within the training module, when the request is received by the system, then the AI-driven response is returned within 2 seconds.
Accurate NLP Understanding
Given a user asks a question about a Pulseboard feature, when processed, then the system returns an answer with at least 90% accuracy as verified by domain expert review.
Integration with Training Module
Given a user is viewing a specific training lesson, when they ask a related question, then the response references the current lesson context and provides relevant guidance.
High Load Performance
Given 100 concurrent user queries, when processing under peak load, then at least 95% of responses are delivered within 2 seconds.
Failure Fallback Mechanism
Given the AI service fails to generate a response, when the error occurs, then the system displays a fallback message to the user and logs the error within 2 seconds.
Context-Aware Guidance
"As a user navigating different modules, I want the virtual coach to offer guidance relevant to my current screen so that I can perform tasks accurately and efficiently."
Description

Analyze the user’s current context within the dashboard—such as the active module, patient record, or scheduling section—and provide tailored guidance and best-practice suggestions relevant to the task at hand. Draw from a curated knowledge base and adapt recommendations based on usage patterns and common pitfalls, helping users navigate complex workflows efficiently.

Acceptance Criteria
Scheduling Module Context Prompts
Given the user is in the Scheduling Module and creating an appointment, when the Virtual Coach is invoked, then the system displays appointment-scheduling best-practice suggestions within 2 seconds; and these suggestions optimize time-slot allocation and reduce overlap risks.
Patient Record Navigation Guidance
Given the user opens a patient record, when the Virtual Coach detects incomplete fields, then it highlights required fields, provides context-aware data-entry tips, and references at least two common pitfalls relevant to the record type.
Billing Section Recommendation
Given the user attempts to generate an invoice in the Billing Section, when mandatory insurance or payment fields are missing or invalid, then the Virtual Coach identifies each missing field, lists the top three related errors, and offers corrective actions within 3 seconds.
Bottleneck Identification Alert
Given the system identifies a scheduling conflict or resource bottleneck, when the conflict arises, then the Virtual Coach alerts the user within 5 seconds, explains the issue, and suggests at least two resolution options based on past usage data.
Complex Workflow Optimization Suggestion
Given the user is performing a multi-step workflow (e.g., processing lab orders), when the user pauses for more than 60 seconds, then the Virtual Coach prompts the next logical step with a rationale and links to relevant knowledge-base articles.
Personalized Learning Paths
"As a new manager, I want the virtual coach to tailor training recommendations based on my learning progress so that I can focus on areas where I need the most help."
Description

Track user interactions and performance metrics to create individualized learning paths that adjust over time. By monitoring frequently asked questions and areas of difficulty, recommend specific tutorials, tips, and practice exercises, accelerating mastery of Pulseboard system features.

Acceptance Criteria
Identify New User Knowledge Gaps
Given a new user completes the initial assessment quiz When the AI analyzes quiz responses Then the system assigns at least three learning modules targeting identified weak areas And the personalized path is generated within 5 seconds
Adjust Learning Path Based on Quiz Performance
Given a user completes a module quiz When the user scores below 80% on any question cluster Then the system adds at least two remedial practice exercises to the learning path And notifies the user of updated recommendations
Recommend Tutorials for Frequently Asked Questions
Given the system logs user questions during training When a question is asked by more than 10% of active users in a week Then the system surfaces a relevant tutorial link in the user’s personalized path And highlights it at the top of recommended resources
Provide Real-time Practice Exercise Suggestions
Given a user struggles with a specific feature (five repeated errors within one session) When the system detects the error pattern Then an in-app suggestion for a targeted practice exercise appears within the chat And the suggestion includes a direct link to launch the exercise
Progress Dashboard Displays Personalized Path Milestones
Given a user views their personalized learning dashboard When milestones are reached (module completion, exercise success rate >90%) Then the dashboard displays completed milestones, next recommended steps, and projected completion time And updates in real-time as the user progresses
Integrated System Data Access
"As a practice manager, I want the coach to reference actual clinic data when giving advice so that I receive practical and actionable guidance."
Description

Securely access relevant real-time clinic data—such as appointment statuses, billing errors, and patient flow metrics—to provide situational advice or warnings. For example, if a scheduling conflict arises, the coach will alert the user and suggest corrective actions, reducing errors and improving operational efficiency.

Acceptance Criteria
Scheduling Conflict Detection Scenario
Given two appointments overlap for the same provider or room, when the virtual coach detects the conflict, then within 5 seconds it shall notify the user of both appointments and recommend at least two corrective actions.
Billing Error Notification Scenario
Given a billing error occurs during patient check-out, when the system logs the error, then within 10 seconds the virtual coach shall alert the user with the error type and provide a minimum of two resolution steps.
Patient Flow Bottleneck Alert Scenario
Given the average patient wait time exceeds the configured threshold, when the threshold is breached, then within 5 minutes the virtual coach shall warn the user, list all affected appointments, and suggest resource redistribution options.
Real-time Data Access Validation Scenario
Given the virtual coach requests appointment statuses, billing errors, or patient flow metrics, when a query is made, then the coach shall retrieve and display data within 2 seconds and ensure no data older than 10 seconds is shown.
Data Retrieval Failure Handling Scenario
Given an integration endpoint is unreachable, when the virtual coach attempts data retrieval, then it shall display a clear error message to the user, log the error, retry up to two times at 30-second intervals, and suggest escalating if failures persist.
Interaction Logging and Analytics
"As a product owner, I want to review analytics on virtual coach usage so that I can optimize training content and enhance the AI assistant’s effectiveness."
Description

Log all user interactions with the virtual coach, capturing queries, responses, resolution rates, and user feedback. Feed this data into analytics dashboards to identify common issues, assess the coach’s performance, and inform ongoing improvements to the knowledge base and AI models.

Acceptance Criteria
User Query Recording
Given a user submits a question to the virtual coach, When the AI assistant receives the query, Then the system logs the query text, user ID, timestamp, and session context into the interaction log.
Response Logging
Given the virtual coach generates a response, When the response is delivered to the user, Then the system logs the response content, associated query ID, response timestamp, and response confidence score.
Feedback Capture
Given a user rates the coach's response or provides feedback, When the feedback is submitted, Then the system logs the feedback rating, comments, query ID, and timestamp.
Dashboard Data Availability
Given interaction logs are stored, When the analytics dashboard is accessed, Then the dashboard displays aggregated metrics such as total queries, average response time, resolution rate, and feedback distribution within 5 seconds.
Performance Metric Tracking
Given historical interaction data exists, When the dashboard filters by date range, Then the system calculates and displays resolution rates, average confidence scores, and identifies top issues correctly for the selected period.

Certification Badges

Awards digital badges and certificates upon successful completion of module groups or the entire onboarding program. These recognitions motivate learners, validate competency, and showcase readiness for independent clinic tasks.

Requirements

Criteria Configuration
"As a practice manager, I want to configure criteria for earning badges so that the recognitions reflect our specific training requirements."
Description

Enable administrators to define and manage the criteria for earning badges by grouping onboarding modules, setting completion thresholds, and assigning weightings. This configuration integrates with the existing course management system to trigger badge issuance automatically once users meet the specified requirements, promoting flexibility in aligning badge awards with organizational training standards.

Acceptance Criteria
Module Group Creation and Management
Given an administrator is on the Criteria Configuration page When they create a new module group with a unique name and select onboarding modules Then the system saves the group and displays it in the module group list
Completion Threshold Setting
Given an administrator configures a badge criteria When they enter a completion threshold value between 0 and 100% Then the system validates, stores the threshold, and displays a success confirmation
Weight Assignment for Modules
Given an administrator assigns weightings to each module in a group When the total weighting sums to exactly 100% Then the system accepts the configuration Otherwise it displays an error indicating the required total
Automatic Badge Trigger on Criteria Met
Given a user completes the required modules When their completion percentage meets or exceeds the configured threshold and weightings Then the system issues the badge automatically and updates the user’s profile with badge details
Editing Existing Badge Criteria
Given an administrator selects an existing badge criteria configuration When they modify module groupings, thresholds, or weightings Then the system saves the updated configuration immediately and logs the change in the audit trail
Automated Badge Generation
"As a learner, I want to receive a digital badge automatically upon completing my onboarding modules so that I can showcase my achievements instantly."
Description

Implement an engine that automatically issues digital badges when users complete the defined module groups or entire onboarding program. The engine will generate badge images, embed metadata (e.g., user name, date, module details), and record issuance in the user’s profile, ensuring immediate and accurate recognition of achievements.

Acceptance Criteria
Module Group Completion
Given a user completes all modules within a module group, when the completion is recorded, then the system generates a digital badge image that includes the user's name, module group name, and issuance date, and records the badge issuance in the user's profile.
Full Program Certification
Given a user completes the entire onboarding program, when program completion is confirmed, then the engine issues the final certification badge with embedded metadata and updates the user's profile immediately.
Badge Metadata Accuracy
When a badge is generated, then the metadata embedded in the badge (user name, module details, and issuance date in ISO 8601 format) matches the corresponding fields in the user's profile record.
Duplicate Badge Prevention
Given a user has already received a badge for a specific module group, when the user completes the same module group again, then the engine does not generate a duplicate badge and logs an event indicating a duplicate issuance attempt.
Badge Image Generation
When the badge engine is invoked for any badge issuance, then the generated badge image is 400x400 pixels, PNG format, and conforms exactly to the approved design template.
Certificate Export and Download
"As a learner, I want to download a PDF certificate of my completed modules so that I can save or print it for my records."
Description

Provide a feature for learners to download PDF certificates that include their name, completion date, badge graphics, and a validating signature or seal. This export integrates with the badge issuance system to populate user-specific data, enabling learners to save, print, or share formal certificates for record-keeping and professional purposes.

Acceptance Criteria
Module Completion Certificate Generation
- Given a learner completes all modules, when they click 'Download Certificate', then the system generates a downloadable PDF certificate. - The PDF contains the learner's full name, module group title, completion date, badge graphics, and validating signature. - The generation action occurs within 5 seconds.
User Data Population on Certificate
- The certificate PDF accurately displays the learner's first and last name exactly as entered in their profile. - The completion date on the certificate matches the date of final module completion. - If the learner's name exceeds 30 characters, it is properly truncated or scaled without overlap.
Certificate Visual Elements Rendering
- The badge graphic appears at the top center of the certificate with a resolution of at least 300 DPI. - The validating signature or seal is displayed at the bottom right corner, legible and correctly positioned. - All images maintain aspect ratio and no visual artifacts are present.
Certificate PDF Download Functionality
- The 'Download Certificate' button triggers a browser download prompt for a PDF file. - The downloaded file name follows 'Certificate_Lastname_Firstname_YYYYMMDD.pdf'. - The PDF is fully accessible and opens without errors in standard PDF viewers.
Email Delivery of Certificate
- Upon completion, the system sends an email with the certificate PDF attached to the learner's registered email within 2 minutes. - The email subject is 'Your Pulseboard Certificate of Completion'. - The email body includes the learner’s name and a congratulatory message.
User Profile Badge Showcase
"As a learner, I want to view all my earned badges on my dashboard so that I can track my progress and accomplishments."
Description

Design and integrate a dashboard component where learners can view all earned badges and certificates in a centralized profile section. The showcase will display badge images, issuance dates, and module details, allowing users to track their progress, review achievements, and access certificate downloads from one intuitive interface.

Acceptance Criteria
Display Badge Gallery in User Profile
Given a logged-in learner with earned badges When navigating to the profile badge showcase Then all badges are displayed in a grid with correct images and names
Access Badge Details and Module Information
Given the badge showcase is visible When the user clicks on a badge Then a details view opens showing module name, completion requirements, and description
Download Certificates from Badge Showcase
Given a badge with an associated certificate When the user clicks the download icon Then the certificate is downloaded as a PDF file named "Badge_<badgeName>_<userName>.pdf"
Show Issue Dates for Each Badge
Given badges have issuance dates stored When viewing the badge showcase Then each badge displays its correct issuance date in MM/DD/YYYY format
Responsive Layout for Badge Showcase
Given different device screen sizes When the user visits the badge showcase Then the layout adapts to display badges in one column on mobile, two columns on tablet, and three columns on desktop
Badge Sharing and Verification
"As a learner, I want to share my badges with colleagues or employers and have them verify its authenticity so that my credentials are recognized."
Description

Develop a secure sharing mechanism that generates unique, verifiable URLs or embed codes for each badge and certificate. Third parties can use these links to confirm authenticity, view issuance details, and validate metadata. This feature supports social sharing, embedding in resumes or professional profiles, and external verification of credentials.

Acceptance Criteria
Generating Unique Badge Shareable Link
Given a learner has completed a badge-eligible module group When the learner clicks the "Share Badge" button Then the system generates a unique, cryptographically secure URL containing a non-guessable token And the system returns the URL within 2 seconds
Providing Embed Code for External Profiles
Given a generated badge share URL When the learner requests embed code Then the system provides an HTML snippet with correct badge image, metadata attributes (badge ID, issuance date, learner name) And the embed code renders the badge correctly in standard HTML pages
Third-Party Badge Verification
Given a third party accesses a valid badge share URL When the URL is opened in any modern browser Then the landing page displays badge image, learner name, issuance date, and issuing organization And the metadata integrity is verified via a digital signature that matches the badge record
Social Media Link Preview
Given a badge share URL When the URL is posted to a social media platform supporting Open Graph or Twitter Card metadata Then the shared link preview displays the badge image, badge title, and issuing organization correctly
Revoking Access to Shared Badges
Given an administrator revokes a learner’s badge When a third party attempts to access the previously issued share URL Then the system returns a 404 Not Found or explicit revocation message within 1 second And no badge data or metadata is exposed

QuickScan Registration

Patients simply scan a personalized QR code at arrival to instantly confirm their appointment and update their status on the live dashboard. This eliminates manual check-in, reduces front desk queues, and accelerates patient flow from the moment they walk in.

Requirements

QR Code Generation
"As a patient, I want to receive a personalized QR code after booking so that I can quickly check in upon arrival without manual verification."
Description

Develop a system to generate unique, patient-specific QR codes linked to appointment records. Ensure the codes are scannable by standard mobile devices and printed on appointment confirmations or emailed securely. The generation process must integrate with the scheduling module to automatically create and distribute codes upon booking confirmation.

Acceptance Criteria
Generation of QR Code Upon Booking Confirmation
Given a patient completes appointment booking, When the booking is confirmed, Then a unique, patient-specific QR code is automatically generated and linked to the appointment record in the scheduling module.
Scannability of QR Codes on Standard Devices
Given the printed or digital QR code is presented, When scanned by a standard mobile device camera, Then the code is recognized and decoded with a success rate of 99% or higher across iOS and Android devices.
Secure Distribution of QR Codes to Patients
Given a confirmed appointment with a patient email address or phone number on file, When the system sends the QR code, Then the code is delivered via secure email or SMS with encryption, and a delivery confirmation is logged in the patient record.
Integration with Scheduling Module for Automated Code Generation
Given the scheduling module receives a new or updated appointment, When the scheduling API triggers the QR generation process, Then the QR code is created within two seconds and a reference to it is stored in the appointment metadata.
Uniqueness and Non-Reusability of QR Codes
Given any two appointment records, When their QR codes are generated, Then each code must be unique and codes associated with past appointments must be invalidated to prevent reuse.
Real-Time Status Update
"As a practice manager, I want the dashboard to reflect patient arrivals immediately so that I can adjust resources and reduce bottlenecks in real time."
Description

Implement functionality to update patient check-in status instantly on the dashboard once a QR code is scanned. This requires establishing a real-time data stream between the scanning endpoint and the dashboard interface. The update should reflect in patient queues, trigger notifications for the clinical staff, and refresh waiting time estimates.

Acceptance Criteria
Patient Arrival Scan
Given a patient scans their personalized QR code at the clinic entrance When the system receives the scan Then the patient's check-in status updates on the dashboard within 2 seconds
Invalid QR Code Scan Attempt
Given a patient scans an invalid or expired QR code When the system processes the scan Then an error message is displayed on the scanning device and no dashboard update occurs
Simultaneous Scans Under Load
Given 50 patients scan their QR codes simultaneously When the system handles concurrent scan events Then all check-in statuses update on the dashboard within 2 seconds per scan with zero failures
Staff Notification on Check-In
Given a patient's status changes to 'Checked In' When the dashboard updates the status Then clinical staff receive a real-time notification within 5 seconds
Automatic Waiting Time Refresh
Given any patient's check-in status change occurs When the dashboard refreshes Then the average waiting time estimate recalculates and displays the updated value within 3 seconds
Error Handling & Retry Mechanism
"As a front-desk staff member, I want clear error messages and a retry option when a QR code fails to scan so that I can assist patients without delaying check-in."
Description

Design robust error detection for failed or invalid QR code scans, providing clear feedback on-screen with retry options. Log scan errors for analysis and support troubleshooting. The system should allow manual override by staff if scans repeatedly fail, ensuring no patient is left unregistered.

Acceptance Criteria
Invalid QR Code Scan
Given a patient scans an invalid or unrecognized QR code, When the system processes the scan, Then it displays an "Invalid QR Code" message within 2 seconds and provides a retry option.
Scan Timeout or Connectivity Error
Given a scan attempt fails due to network issues or device timeout, When the timeout occurs, Then the system displays a "Scan Failed: Network Error" notification within 3 seconds and shows a retry button.
Repeated Scan Failures with Manual Override
Given three consecutive scan failures for the same appointment, When the third failure is detected, Then the system enables a manual override button allowing staff to register the patient manually and records the override event.
Error Logging for Failed Scans
Given any scan failure event, When the failure occurs, Then the system logs the error details (timestamp, appointment ID, error type) to the central error log accessible in the admin dashboard.
Successful Retry After Initial Failure
Given an initial scan fails and the user selects retry, When the retry scan succeeds, Then the system updates the patient's status on the live dashboard within 5 seconds.
Dashboard Integration
"As a clinic manager, I want QuickScan check-ins visible on the main dashboard so that I have a consolidated view of patient flow and can generate reports easily."
Description

Ensure the QuickScan module seamlessly integrates with the existing Pulseboard dashboard. Patient status changes, timestamps, and scan analytics must display in the patient flow section without performance degradation. Include filters to view only QuickScan-checked patients and aggregate metrics for reporting.

Acceptance Criteria
Real-time Status Update on Dashboard
Given a patient scans their personalized QR code at check-in, When the scan is processed, Then the patient's status changes to 'Checked In' on the live dashboard within 1 second.
QuickScan Patient Filter Functionality
Given the dashboard filter is set to 'QuickScan Only', When a user applies the filter, Then only patients who checked in via QuickScan are displayed, and all non-QuickScan patients are hidden.
Timestamp Accuracy Display
Given a QuickScan event occurs, When the event is logged, Then the timestamp displayed on the patient flow dashboard matches the actual scan time to within 2 seconds.
Scan Analytics Aggregation
Given the admin views the QuickScan analytics report, When the report is generated, Then total scans, average check-in time, and scans per hour are displayed correctly for the selected date range.
Performance Under Peak Load
Given 100 simultaneous QuickScan events, When these scans occur within a 5-minute window, Then the dashboard performance (page load and update latency) remains under 2 seconds for all updates.
Security & Privacy Compliance
"As a compliance officer, I want patient check-in data protected and auditable so that the clinic adheres to regulatory requirements."
Description

Incorporate data encryption and access controls for QR code data in transit and at rest to comply with HIPAA and other healthcare regulations. Implement role-based access to scan logs and appointment data. Provide audit trails for all scan events to ensure traceability and accountability.

Acceptance Criteria
Encrypted QR Code Transmission
Given a patient scans a QR code, When the data is sent to the backend, Then the transmission must be encrypted using TLS 1.2 or higher with AES-256 encryption.
Encrypted Data at Rest
Given QR code data is stored in the database, Then the data must be encrypted at rest using AES-256 encryption and decryptable only by authorized services.
Role-Based Access Control Enforcement
Given a user attempts to access scan logs, When the user has the 'Admin' role, Then access is granted; otherwise access is denied.
Audit Trail Event Logging
Given any scan event occurs, Then an immutable audit log entry must be created containing timestamp, user ID, event type, and QR code data reference.
Audit Log Integrity Verification
Given an audit log entry is modified, Then the system must detect the change and flag the entry as tampered for review.

Smart Queue Assignment

Upon scanning the QR code, the system automatically categorizes patients by appointment type and assigns them to the correct virtual queue. This ensures patients are routed to the right department or clinician without staff intervention, minimizing delays and confusion.

Requirements

QR Code Scanning Engine
"As a patient, I want the system to recognize and decode my QR code upon arrival so that my appointment details are automatically captured without manual check-in."
Description

Implement a robust QR code scanning module that accurately reads and decodes patient QR codes at registration kiosks or mobile devices, ensuring reliable capture of patient ID and appointment metadata under varying lighting and device conditions.

Acceptance Criteria
Successful scan under optimal conditions
Given a standard printed QR code under normal lighting (300–500 lux) and at a distance of 20–30 cm, When the user initiates the scan, Then the system decodes patient ID and appointment metadata with 100% accuracy within 2 seconds.
Scan under low-light environment
Given the QR code is presented under lighting levels down to 50 lux, When the user scans the code, Then the system successfully decodes the data with at least 95% accuracy.
Scan with angled QR code
Given the QR code is tilted or rotated up to 30 degrees on any axis, When scanned by the module, Then the system decodes patient information with at least 98% accuracy.
Scan with damaged QR code
Given a QR code with up to 10% surface damage (e.g., scratches, smudges), When the user attempts a scan, Then the system retrieves the correct patient ID and metadata at least 90% of the time.
Cross-device compatibility scanning
Given the QR code is scanned on mobile devices (iOS and Android) with camera resolutions between 8MP and 12MP, When the user scans the code, Then the system decodes the data correctly within 3 seconds on at least 95% of attempts.
Appointment Type Classification
"As a practice manager, I want the system to accurately classify appointment types so that patients are routed to the correct service stream without staff intervention."
Description

Develop logic to interpret decoded appointment data and classify patients by appointment type (e.g., consultation, follow-up, imaging), enabling downstream routing rules to operate on structured, reliable categorization.

Acceptance Criteria
Categorize New Consultation Appointment
Given a patient scans the QR code for a consultation appointment with valid encoded data, when the system decodes the QR code, then the appointmentType field is set to 'Consultation' and the patient is added to the consultation queue within 1 second.
Classify Follow-Up Appointments
Given a returning patient scans the QR code indicating a follow-up appointment, when the system parses the appointment data, then the appointmentType is classified as 'Follow-Up' and routing rules direct the patient to the follow-up queue.
Route Imaging Appointments
Given a patient has an imaging appointment encoded in the QR code, when the system decodes and classifies the appointment, then the patient is assigned to the imaging queue and an alert is logged for imaging department staff.
Handle Unknown Appointment Types
Given the decoded QR code contains an unrecognized appointment type, when the classification logic evaluates the data, then the appointmentType is set to 'General' and a flag is generated for manual staff review.
Real-Time Classification Under Load
Given 100 concurrent QR code scans within one minute, when the classification service processes the scans, then 99% of appointments are correctly classified and queued within 1 second of scan time.
Automated Queue Assignment
"As a front-desk user, I want patients to be placed in the right virtual queue automatically after scanning so that I don’t have to manage queue assignments manually."
Description

Create a service that maps classified appointment types to virtual queues and assigns incoming patients automatically, updating queue membership in the backend without manual input.

Acceptance Criteria
Standard Appointment Queue Assignment
Given a patient scans a valid QR code for a scheduled consultation appointment, when the system receives the classification, then the patient is automatically added to the "Consultation" virtual queue and the queue count increments by one.
Multiple Concurrent Scans
Given two or more patients scan their QR codes for different appointment types within one second, when the backend processes each classification, then each patient is assigned to their respective queues without any assignment conflicts or processing delays.
Unrecognized Appointment Type Handling
Given a patient scans a QR code with an appointment type not present in the mapping table, when the system processes the classification, then the patient is routed to the "General Inquiry" queue, and an alert is logged indicating an unmapped appointment type.
Real-Time Queue Update Reflection
Given a patient is assigned to a queue, when the assignment is successful in the backend, then the updated queue membership and new queue position are reflected within two seconds on the manager’s live dashboard.
Database Transaction Integrity
Given the automated assignment service is invoked, when multiple assignments occur simultaneously, then all queue assignment transactions complete successfully with no lost or duplicate records in the queue database.
Department Routing Interface
"As a clinic staff member, I want appointment queues to map directly to my department or clinician schedule so that I can see which patients are expected without cross-referencing multiple systems."
Description

Design an interface layer that translates virtual queue assignments into department and clinician routing, maintaining configuration data for clinics to customize mappings and ensuring patients land with the correct care teams.

Acceptance Criteria
Automatic Department Routing
Given a patient scans the check-in QR code linked to appointment type 'Physical Therapy', when the system processes the check-in, then the patient is assigned to the 'Physical Therapy Department' queue as configured.
Custom Mapping Update
Given an admin updates the appointment-to-department mapping in the configuration panel, when the admin saves the changes, then the new mapping is persisted and used for subsequent routing without system errors.
Fallback Assignment on Missing Mapping
Given a patient scans the QR code with an appointment type that has no mapping configured, when routing is attempted, then the system assigns the patient to the default 'General Triage' queue and logs a warning alert.
Clinician Queue Assignment
Given the appointment mapping includes a specific clinician for follow-up appointments, when the system routes the patient, then they are placed in the virtual queue of the designated clinician.
Configuration Data Load on Launch
Given the Pulseboard application is restarted or refreshed, when the department routing interface initializes, then all clinic-specific mappings are loaded correctly from persistent storage.
Real-Time Dashboard Integration
"As a practice manager, I want the dashboard to reflect queue changes instantly so that I can identify delays and reallocate resources proactively."
Description

Integrate queue assignment events into the Pulseboard dashboard in real time, allowing practice managers and staff to monitor patient flow, capacity, and bottlenecks through live updates and visual indicators.

Acceptance Criteria
Real-Time Queue Assignment Update
Given a patient scans their QR code When the system assigns them to a queue Then the dashboard displays the new assignment on the clinician's panel within 2 seconds
Capacity Alert Visualization
Given a queue reaches 90% of its maximum capacity When the threshold is exceeded Then the dashboard shows a yellow warning icon next to the queue name
Bottleneck Indicator Highlight
Given the average wait time in any queue exceeds 10 minutes When this condition is detected Then the dashboard highlights the queue in red and logs an alert
Live Patient Flow Chart Refresh
Given new queue assignments occur continuously When multiple patients are assigned in a sequence Then the dashboard's flow chart updates without requiring manual refresh and maintains data consistency
High-Load Performance
Given 50 simultaneous queue assignments in under one minute When the system processes these events Then the dashboard updates each assignment in real time without latency exceeding 5 seconds
Error Handling and Fallback Routing
"As a receptionist, I want the system to alert staff when automatic routing fails so that we can manually assign the patient and avoid service delays."
Description

Implement error detection for failed scans or classification mismatches with a fallback process that flags issues to staff, provides clear recovery options, and prevents patients from being lost in the workflow.

Acceptance Criteria
QR Code Scan Failure Handling
Given a patient scans a QR code that fails to decode, when the scan result returns an error, then the system shall display a clear ‘Scan Failed’ message with options to retry or seek assistance within 5 seconds.
Classification Mismatch Detection
Given the system classifies a patient’s appointment type incorrectly, when the classification confidence score falls below 80%, then the system shall flag the mismatch, route the patient to a manual review queue, and notify staff within 3 seconds.
Fallback Routing Notification to Staff
Given a fallback route is triggered, when a patient cannot be assigned automatically, then the system shall send a real-time alert to the assigned staff member’s dashboard and mobile app, including patient details and error reason.
Patient Recovery Option Display
Given an assignment error occurs, when the patient views the fallback prompt, then the system shall display at least two recovery options (e.g., rescan QR, contact reception) and guide the patient through the chosen option step-by-step.
System Logging and Alerting for Failed Assignments
Given any scan or classification error, when fallback routing is initiated, then the system shall log the event with timestamp, patient ID, error type, and resolution status, and send a daily summary report to the operations team.

Pre-Visit Prep

After check-in, patients receive an automated link to complete pre-visit forms, insurance details, and health questionnaires. This feature streamlines administrative tasks before the appointment, reduces paperwork at the clinic, and boosts data accuracy for clinicians.

Requirements

Automated Form Delivery
"As a clinic manager, I want the system to automatically send pre-visit forms to patients after check-in so that I can reduce on-site paperwork and ensure forms are completed timely."
Description

After patient check-in, the system automatically generates and sends a secure link containing all required pre-visit forms—health questionnaires, insurance details, and consent documents. This functionality minimizes in-clinic paperwork, accelerates administrative workflows, and integrates completed data directly into the patient’s profile on the dashboard for clinician review.

Acceptance Criteria
Automated Link Generation Post Check-In
Given a patient completes check-in, when check-in is confirmed, then the system generates and sends a unique secure link within 30 seconds via the patient’s preferred channel; Link expiration is configurable and defaults to 24 hours.
Secure Form Access via Link
Given the patient clicks the link within its validity period, when accessed, then the patient is presented with all required pre-visit forms over a secure HTTPS connection; No additional login credentials are required beyond the unique link token.
Pre-Visit Form Completion and Submission
Given the patient fills out all mandatory fields, when the patient submits the forms, then the system validates inputs, displays inline error messages for invalid or missing data, and shows a success confirmation upon valid submission.
Data Auto-Integration into Dashboard
Given the forms are submitted successfully, when data is received, then the system maps responses into the patient’s profile on the clinician dashboard within 60 seconds; Dashboard updates appear in real time without requiring manual page refresh.
Link Resend on Request
Given the patient or staff requests a resend of the form link before expiration, when the request is made, then the system issues a new secure link with updated expiration and logs the resend action in the activity audit trail.
Secure Data Capture
"As a practice manager, I want patient-submitted pre-visit data to be captured securely and validated in real time so that clinician data integrity and privacy are maintained."
Description

Pre-visit forms must utilize end-to-end encryption during transmission and storage, adhere to HIPAA compliance standards, and include real-time validation rules to detect missing or invalid entries. Captured data should sync seamlessly with the electronic health record (EHR) module to maintain integrity and privacy.

Acceptance Criteria
Encrypted Data Transmission and Storage
All patient pre-visit form data is encrypted in transit using TLS 1.3 and at rest with AES-256 and verified by automated security tests.
HIPAA Compliance Enforcement
System maintains audit logs for every access and modification of pre-visit data and enforces role-based access controls, meeting HIPAA requirements.
Real-Time Data Validation
Form cannot be submitted until all required fields are populated with valid data according to predefined validation rules and displays inline error messages.
Seamless Sync with EHR
Submitted data syncs with the EHR module within 2 seconds without data loss or duplication, verified by record ID matching.
Error Handling and User Notification
If encryption, transmission, or sync fails, the patient sees a clear error message and the system logs the error and retries automatically.
Insurance Verification Integration
"As a billing specialist, I want the system to automatically verify patient insurance information after they submit forms so that we can identify coverage issues before appointments."
Description

Integrate with third-party insurance APIs to automatically verify patient insurance information submitted through pre-visit forms. Verification results and any discrepancies should be highlighted on the dashboard, allowing billing staff to address coverage issues before the appointment.

Acceptance Criteria
Successful Insurance Verification
Given a patient submits valid insurance details in pre-visit forms, when the system sends a verification request to the insurance API, then the system receives a successful verification response and displays the patient’s insurance status as "Verified" on the dashboard within 10 seconds.
Invalid Insurance Details Handling
Given a patient submits insurance details with missing or incorrect information, when the system processes the verification request, then the system flags the entry as "Discrepancy Detected", highlights the erroneous fields in red on the dashboard, and logs the specific error message returned by the API.
API Unavailability Response
Given the third-party insurance API is unreachable or returns a 5xx error, when the system attempts verification, then the system retries the request up to 3 times with 5-second intervals, and after the final failure displays an "API Unavailable" alert on the dashboard, allowing billing staff to manually verify.
Partial Coverage Alert
Given the insurance API indicates partial coverage for certain services, when the verification completes, then the system displays a "Partial Coverage" warning badge next to the affected service types and calculates and shows estimated patient responsibility amounts.
Verification Audit Logging
Given any insurance verification transaction completes, when the verification results are returned, then the system logs the timestamp, patient ID, API response code, and response time in an audit log that can be exported as a CSV file.
Real-Time Completion Reminders
"As a clinic manager, I want to send automated reminders to patients who haven't completed pre-visit forms so that we maximize form completion rates and avoid visit delays."
Description

Implement an automated reminder engine that sends email and SMS notifications at configurable intervals (e.g., 72, 48, and 24 hours before the appointment) to patients who have not completed their pre-visit forms. Reminder frequency and channel preferences should be adjustable in the settings.

Acceptance Criteria
72-Hour Reminder Dispatch
Given a patient has an appointment in 72 hours and has not completed pre-visit forms When the reminder engine runs at the 72-hour interval Then the system sends a reminder to the patient via their preferred channel and logs the dispatch event
Post-Reminder Completion Cancellation
Given a patient received a reminder and completes all pre-visit forms before the next scheduled reminder When the system checks form completion status at the next interval Then no further reminders are sent and the system logs the cancellation of pending reminders
Channel Preference Enforcement
Given a patient has selected SMS as their preferred notification channel and has pending reminders When the reminder engine triggers a notification Then the system sends the reminder only via SMS and does not send an email
Reminder Configuration Update
Given a clinic admin updates reminder intervals and channel preferences in settings When the admin saves the new configuration Then the system persists the settings and applies the new intervals and channels for all subsequent reminder dispatches
Reminder Delivery Failure Logging
Given the SMS gateway returns a delivery failure response when sending a reminder When the system processes the failure Then it logs the error with timestamp, appointment ID, and retry count, and schedules a retry according to the defined retry policy
Mobile-Optimized Form Interface
"As a patient, I want to complete my pre-visit forms easily on my mobile device so that I can fill them out conveniently before my appointment."
Description

Design pre-visit forms with a responsive layout and mobile-first UI components, including progress indicators, auto-save functionality, and touch-friendly input controls. Ensure compatibility across major mobile browsers to provide patients a seamless form-filling experience on smartphones and tablets.

Acceptance Criteria
Progress Indicator Visibility
Given a patient is completing the form on a mobile device When they navigate between form sections Then a persistent progress bar is displayed at the top showing the current step and percentage completion
Auto-Save Data Persistence
Given a patient is entering form data When they pause for longer than 30 seconds or lose connection Then the system automatically saves the entered data and restores it upon return without data loss
Touch-Friendly Input Controls
Given a patient uses a tablet When they interact with form fields Then all touch targets meet a minimum size of 44x44 pixels and controls respond accurately to tap gestures
Responsive Layout on Major Mobile Browsers
Given a patient accesses the form on any major mobile browser When the device orientation changes Then the layout adjusts without horizontal scrolling and all elements remain fully visible and functional
Form Navigation Buttons Functionality
Given a patient navigates through multi-page forms When they tap the Back or Next button Then the form transitions to the previous or next section and displays the correct progress indicator without losing entered data

Real-Time ETA

Integrated with live dashboard analytics, this feature displays an estimated wait time to patients via their smartphone or kiosk. By setting realistic expectations, it enhances patient satisfaction, reduces perceived wait times, and lowers no-show rates.

Requirements

Real-Time Data Aggregation
"As a practice manager, I want the ETA system to pull live scheduling and service data so that wait time estimates remain accurate and up-to-date."
Description

Implement continuous extraction and normalization of appointment, check‐in, and service duration data from the clinic’s core scheduling and POS systems to provide up-to-the-second information for ETA computation. This requirement ensures that the ETA feature has accurate, live inputs by handling data polling intervals, API integrations, and data consistency checks.

Acceptance Criteria
Continuous Data Extraction from Scheduling System
Given the scheduling system is online When the data aggregation service polls at a 30-second interval Then 100% of new and updated appointment records within the last interval must be retrieved without duplication or omission.
Real-Time POS Transaction Polling
Given the POS system endpoint is reachable When the aggregation service requests transaction data Then the service must successfully fetch and parse all completed service durations with 99.9% uptime and log any failures for retry.
Data Normalization and Format Validation
Given raw data from scheduling and POS systems When the aggregation pipeline processes incoming records Then all date-time fields must be converted to UTC ISO 8601 format and patient identifiers must match the master patient index.
API Integration Error Handling
Given any API response returns an error code or malformed payload When the aggregation service receives the response Then the service must retry up to three times with exponential backoff and emit an alert if it still fails.
Latency Threshold Monitoring
Given continuous data flow When measuring end-to-end data ingestion time Then the total latency from original event to availability in the ETA engine must not exceed 5 seconds for 95% of transactions per hour.
ETA Calculation Engine
"As a patient, I want to receive an accurate expected wait time so that I can plan my arrival and reduce uncertainty."
Description

Develop a predictive algorithm that calculates individualized patient wait times by analyzing current queue length, average service durations, resource availability, and real-time updates. The engine must dynamically adjust estimates as new data arrives and factor in variability for different appointment types.

Acceptance Criteria
Standard Appointment Queue
Given a patient checks in for a 30-minute appointment When the queue length, average service duration, and resource availability are analyzed Then the engine displays an ETA within ±2 minutes of the actual wait time for 90% of patients
Resource Reassignment
Given a provider becomes available earlier than scheduled When the engine receives the real-time status update Then the ETAs of all waiting patients are recalculated and updated within 30 seconds
Appointment Type Variation
Given appointments of different types (e.g., consultation, follow-up, procedure) When calculating ETAs Then the engine applies the correct average service duration template associated with each appointment type
Surge Hour Load
Given peak clinic hours with over 50% capacity load When multiple check-ins and updates occur simultaneously Then the engine processes recalculations within 60 seconds and maintains ETA accuracy within ±3 minutes for 95% of cases
Patient Notification Update
Given a patient’s ETA changes by more than 2 minutes When the recalculated ETA is available Then the system pushes an update notification to the patient’s device or kiosk within 10 seconds
Patient Notification Delivery
"As a patient, I want to receive my updated wait time on my smartphone so that I can know when to arrive at the clinic."
Description

Create a notification service that sends calculated ETAs to patients via multiple channels (mobile app push notifications, SMS, and kiosk display). The service should support template-based messages, real-time updates, and retry logic for failed deliveries.

Acceptance Criteria
Initial ETA Notification Delivery via Mobile App
Given a patient has a valid mobile device token and an ETA is calculated, when the ETA is updated, then a push notification containing the ETA using the template 'Your estimated wait time is {ETA}' is sent successfully to the patient's mobile app within 10 seconds.
Fallback to SMS for Failed Push Notification
Given push notification delivery fails for the patient's mobile app, when the system retries delivery, then an SMS containing the ETA is sent using the SMS template within 30 seconds of the initial failure.
Kiosk Display Update for On-site Patients
Given a patient checks in at a kiosk, when the ETA changes by more than 2 minutes, then the kiosk display updates the ETA within 5 seconds and shows the new time in a visible section.
Template-based Message Integrity
Given any channel (push, SMS, kiosk) and the configured message templates, when a notification is generated, then the message content matches the template placeholders replaced with correct ETA values and clinic name.
Retry Logic Limits
Given a notification fails delivery, when retries are executed, then the system attempts delivery up to 3 times with exponential backoff and logs each attempt's status.
Dashboard ETA Visualization
"As a practice manager, I want to see a visual representation of all patient wait times so that I can identify delays and reassign resources proactively."
Description

Enhance the practice manager’s dashboard to display patient ETAs with intuitive visual indicators (e.g., color codes, countdown timers). Include filtering and sorting by appointment type, provider, or urgency, allowing managers to quickly identify potential bottlenecks.

Acceptance Criteria
Delayed ETA Visual Indicator
Given a patient ETA exceeds the scheduled appointment time by 1 minute or more, When the dashboard is displayed, Then the patient's ETA entry is highlighted in red. Given a patient ETA is within ±5 minutes of the scheduled time, When the dashboard is displayed, Then the ETA entry is highlighted in yellow. Given a patient ETA is 5 minutes or more ahead of schedule, When the dashboard is displayed, Then the ETA entry is highlighted in green.
Provider-Based ETA Filtering
Given multiple providers have scheduled appointments, When the manager selects a specific provider from the filter dropdown, Then only ETAs for that provider are displayed. Given a provider filter is active, When the manager clears the filter, Then all patient ETAs are displayed again.
Urgency Sorting for Bottleneck Identification
Given patient appointments are tagged with urgency levels (routine, urgent, emergency), When the manager sorts by urgency, Then ETAs are reordered with the highest urgency appointments at the top of the list.
Countdown Timer Accuracy
Given a patient's scheduled appointment time is set, When the dashboard updates ETAs, Then the countdown timer decreases in one-minute increments and reflects server time within ±5 seconds accuracy. Given the dashboard reconnects after a network interruption, When new ETA data is received, Then the countdown timer recalculates and displays the correct remaining time.
Appointment Type Color-Coding
Given different appointment types (consultation, follow-up, procedure), When the dashboard displays ETAs, Then each appointment type is represented by a unique color code and the legend clearly maps colors to types.
Error Handling and Fallback Mechanism
"As a system administrator, I want the ETA feature to handle data errors gracefully so that patients and staff always see a fallback estimate and administrators are notified of issues."
Description

Implement robust error detection and failover logic for scenarios such as data outages, API failures, or anomalous input values. Provide default messaging when real-time data is unavailable and generate alerts for system administrators.

Acceptance Criteria
API Failure During ETA Retrieval
Given the Real-Time ETA feature requests data from external API and the API returns a failure response, then the dashboard displays a default message 'ETA currently unavailable', logs the error with timestamp, and notifies administrators within 1 minute.
Data Outage at Dashboard
Given the live dashboard experiences a data feed outage for over 30 seconds, then the patient-facing interface displays 'Estimated wait times unavailable', continues to accept appointments, and triggers an alert to the system admin panel.
Anomalous Input Values Detected
Given the incoming wait time value exceeds 180 minutes or is negative, then the system ignores the anomalous value, reverts to last known valid ETA, logs the anomaly detail, and sends notification to the data integrity team.
Fallback to Cached ETA
Given real-time data is unavailable, then the system retrieves the most recent cached ETA, displays it to patients with a note 'Based on last available data', and ensures the cache is not older than 10 minutes.
Administrator Alert on Repeated Failures
Given three consecutive failures of ETA data retrieval within a 5-minute window, then the system escalates an alert email to the on-call administrator, including error logs and retry statistics.
Security and Compliance Assurance
"As a compliance officer, I want the ETA feature to secure patient information so that we maintain regulatory compliance and protect privacy."
Description

Ensure all patient data used in ETA calculations and notifications is handled in accordance with HIPAA and relevant data privacy regulations. Implement encryption in transit and at rest, access controls, and audit logging.

Acceptance Criteria
Data Encryption in Transit Validation
Given ETA data containing patient identifiers is transmitted from the server to the client's device over the network When the data transfer is initiated Then the connection uses TLS 1.2+ encryption and the data packet is encrypted in transit
Data Encryption at Rest Verification
Given ETA calculations and notification data are stored in the database When data is persisted Then the data is encrypted at rest using AES-256 encryption and only decrypted upon authorized access
Access Control and Authentication Enforcement
Given a system user attempts to view or modify ETA data When the user is not authenticated or lacks the required role Then access is denied and the system returns a 403 Forbidden response
Audit Logging and Monitoring
Given any read or write operation on ETA-related patient data When the operation completes Then an immutable audit log entry is created including user ID, timestamp, operation type, and resource ID
HIPAA Compliance Data Access Review
Given an authorized compliance officer requests access to ETA data for an audit When access is granted Then the system logs the request and provides only the minimum necessary PHI fields as per HIPAA's minimum necessary standard

Check-In Insights

Generates comprehensive analytics on daily check-in patterns, peak arrival times, and average processing durations. Clinic managers can leverage these insights to optimize staffing, adjust scheduling windows, and continuously improve patient flow efficiency.

Requirements

Data Aggregation Engine
"As a clinic manager, I want the system to automatically aggregate all check-in data into a single, reliable source so that I can trust the analytics and avoid time-consuming manual data consolidation."
Description

The system must collect and normalize check-in data from multiple sources (front desk input, kiosk scans, mobile app submissions) in real time, store it in a centralized repository, and ensure data consistency and integrity. This functionality enables downstream analytics modules to access up-to-date, accurate information for generating insights on patient arrivals and processing times, reducing manual data handling and eliminating synchronization errors.

Acceptance Criteria
Real-Time Front Desk Data Ingestion
Given a check-in record is entered manually at the front desk, When the record is sent to the Data Aggregation Engine, Then it is normalized and stored in the central repository within 2 seconds. Given 100 simultaneous front desk submissions, When processed, Then the system processes all without errors and maintains data integrity.
Kiosk Scan Data Normalization
Given a barcode scan from a kiosk is received, When the engine ingests the raw scan data, Then the patient ID, timestamp, and visit details are normalized to match the internal schema. Given malformed kiosk data, When normalization fails, Then the record is flagged and logged for review without impacting other processing.
Mobile App Submission Integration
Given a patient submits a check-in via the mobile app, When the Data Aggregation Engine receives the submission, Then it maps all fields correctly and stores the record. Given duplicate submissions from the mobile app, When processed, Then only a single normalized record is created in the repository.
Central Repository Consistency Check
Given check-in data has been aggregated from all sources over the last hour, When a reconciliation job runs, Then the count of records per source matches the count in the central repository. Given any discrepancies in counts, When identified, Then the system generates a discrepancy report for manual review.
Error Handling and Recovery for Source Failures
Given a source endpoint becomes unreachable, When ingestion attempts fail, Then the engine retries up to three times with exponential backoff. Given persistent ingestion failures beyond retries, When threshold is reached, Then the system logs the failure, queues the records, and generates an alert to the operations team.
Peak Arrival Analytics
"As a practice manager, I want to see visual reports of peak patient arrival times so that I can schedule staff more effectively and minimize wait times during busy periods."
Description

The system must analyze aggregated check-in timestamps to identify daily, weekly, and monthly peak arrival periods, display them in interactive visualizations (heatmaps, line graphs), and allow filtering by date range and clinic location. This enables practice managers to recognize high-traffic intervals and adjust scheduling windows or staffing levels proactively to reduce patient wait times and optimize resource allocation.

Acceptance Criteria
Visualize Daily Peak Arrival Times
Given the practice manager selects 'Daily' view on the Peak Arrival Analytics dashboard, when the system aggregates all check-in timestamps for the selected day, then the dashboard displays a heatmap and a line graph with 15-minute time slots, highlights the top three peak intervals by shading, and lists each interval's start time, end time, and check-in count.
Analyze Weekly Peak Periods
Given the practice manager selects 'Weekly' view, when the system processes check-in timestamps for the past seven days, then a line graph plots daily peak check-in volumes, the day with the highest overall check-ins is highlighted, and a table summarizes the peak time window and check-in count for each day.
Identify Monthly Peak Arrival Windows
Given the practice manager selects 'Monthly' view, when the system aggregates check-in timestamps for the selected month, then the dashboard displays a heatmap with days on the vertical axis and hourly slots on the horizontal axis, highlights the five busiest hourly windows across the month, and provides a summary of their dates, times, and counts.
Filter Peak Analytics by Date Range
Given the practice manager inputs a custom date range using the date picker, when the system validates the range and retrieves the corresponding check-in data, then all visualizations update to reflect only data within the selected range, and the title of each chart displays the chosen start and end dates.
Display Peak Arrivals by Clinic Location
Given the practice manager selects a specific clinic location from the location filter dropdown, when the system applies the filter, then all peak arrival visualizations (daily, weekly, monthly) update to display data solely for the selected location, and the location name appears prominently in the dashboard header.
Processing Duration Metrics
"As a clinic manager, I want to track how long it takes patients to complete check-in so that I can identify bottlenecks and streamline the front-desk workflow."
Description

The system must calculate key metrics on check-in processing durations, including average, median, 90th percentile, and outlier handling, and present trends over configurable time intervals. By tracking these metrics, clinic managers can pinpoint inefficiencies in the check-in process, measure the impact of process changes, and drive continuous improvements in patient flow and front-desk performance.

Acceptance Criteria
Real-Time Bottleneck Alerts
"As a clinic manager, I want to receive immediate notifications when check-in wait times exceed acceptable limits so that I can intervene and reassign staff to reduce patient delays."
Description

The system must monitor live check-in queues and processing times, trigger configurable alerts (SMS, email, in-app notifications) when predefined thresholds are exceeded (e.g., wait times over 15 minutes, queue length over 5 patients), and provide actionable recommendations to alleviate congestion. This proactive alerting prevents prolonged delays, ensuring a smoother patient experience and enabling swift operational adjustments.

Acceptance Criteria
Exceed Maximum Wait Time Threshold
Given real-time monitoring is active and the maximum patient wait time threshold is set to 15 minutes When any patient's check-in wait time exceeds 15 minutes Then the system sends an SMS, email, and in-app notification to the clinic manager within 1 minute of the threshold breach
Exceed Maximum Queue Length
Given real-time monitoring is active and the maximum queue length threshold is set to 5 patients When the number of patients in the check-in queue exceeds 5 Then the system sends an SMS, email, and in-app notification to the clinic manager within 1 minute of the threshold breach
Threshold Configuration Changes
Given the clinic manager navigates to the alert settings page When the manager updates the wait time or queue length thresholds and selects notification channels Then the system applies the new settings immediately, persists them in the configuration, and displays a confirmation message
Alert Acknowledgment
Given an alert notification has been received by the clinic manager in-app When the manager clicks “Acknowledge” on the notification Then the system updates the alert status to “Acknowledged,” stops further notifications for that alert instance, and logs the acknowledgment timestamp
Actionable Recommendations with Alerts
Given an alert is triggered for either wait time or queue length threshold breach When the system sends the alert notification Then the notification includes at least two context-specific recommendations (e.g., open an additional check-in station, reassign staff member) based on current queue and processing data
Staffing Optimization Recommendations
"As a clinic manager, I want the system to recommend the ideal number of front-desk staff for upcoming shifts so that I can maintain efficient patient flow without overstaffing."
Description

The system must utilize historical and real-time check-in data to generate AI-driven staffing recommendations, suggesting optimal staff counts for specific time slots, days of the week, and clinic locations. Recommendations should factor in arrival patterns, average processing durations, and special events, enabling managers to make data-informed scheduling decisions that balance service quality and labor costs.

Acceptance Criteria
High Volume Morning Check-Ins
Given historical data showing more than 30 check-ins between 8:00 AM and 10:00 AM When generating staffing recommendations Then the system suggests at least one additional front desk staff and one clinical assistant with a confidence level of 90% or higher
Special Event Day Staffing
Given a scheduled clinic health fair event on a specific date When computing staffing recommendations Then the system factors in a 20% increase in average arrivals and suggests corresponding staff adjustments
Weekday vs Weekend Staffing Patterns
Given historical arrival patterns indicating 15% lower weekend volume When generating staffing recommendations Then the system outputs separate staffing plans for weekdays and weekends reflecting the observed volume differences
Real-Time Surge Response
Given real-time check-in data shows a 25% surge above the hourly average When updating recommendations Then the system issues an alert and recommends adding at least one floater staff within 15 minutes
Peak Time Slot Optimization
Given aggregated check-in durations and arrival patterns for each 30-minute slot When producing recommendations Then the system outputs an optimized staffing plan that ensures average patient wait time remains below 10 minutes
Customizable Insights Dashboard
"As a practice manager, I want to configure my dashboard with the specific analytics and alerts that matter to my clinic so that I can focus on the metrics that drive my daily decisions."
Description

The system must provide a user-friendly dashboard interface where clinic managers can customize the layout, select the analytics widgets they need (peak arrival times, processing durations, staffing recommendations), set custom thresholds for alerts, and save personalized views. This ensures that each practice manager can tailor the insights to their operational priorities and quickly access the most relevant data.

Acceptance Criteria
Personalized Dashboard Creation
Given the clinic manager is on the 'Customize Dashboard' page, when they rearrange widgets and adjust layout settings and click 'Save', then the dashboard displays the new layout immediately and persists after page reload.
Analytics Widget Selection
Given the manager opens the widget library, when they select or deselect the 'Peak Arrival Times', 'Processing Duration', or 'Staffing Recommendations' widgets and click 'Apply', then only the chosen widgets appear on the dashboard.
Threshold Alert Configuration
Given the manager accesses the thresholds settings for a widget, when they enter a valid numeric threshold value and activate alerts, then the system triggers an alert notification when the corresponding metric exceeds the threshold in real time.
Saving and Loading Views
Given the manager has configured a custom dashboard view, when they name and save the view, then it appears in the 'Saved Views' list and can be loaded from there, restoring the exact widget arrangement and settings.
Persistence Across Sessions
Given the manager has saved a custom dashboard view, when they log out and log back in, then the default or last used custom view loads automatically, reflecting the saved configuration.

Unified Queue

Seamlessly merges virtual and in-person appointment streams into a single, prioritized queue. By unifying access points, clinic managers gain a holistic view of upcoming appointments, reducing scheduling conflicts and improving clinician utilization.

Requirements

Centralized Appointment Aggregation
"As a clinic manager, I want to view all virtual and in-person appointments in one consolidated list so that I can efficiently manage patient flow without switching between systems."
Description

Aggregate virtual and in-person appointments into a single queue by normalizing data from all scheduling modules (time, patient ID, location, clinician). Sync data every minute via API to ensure the unified view is always current. This eliminates manual lookups, reduces scheduling errors, and provides managers with one pane-of-glass visibility for all upcoming appointments.

Acceptance Criteria
Minute-Level Appointment Refresh
Given new or updated appointments in any scheduling module, when the system syncs via API at one-minute intervals, then within 60 seconds the unified queue reflects these changes accurately, including time, patient ID, location, and clinician.
Appointment Queue Ordering
Given a mix of virtual and in-person appointments, when loaded into the unified queue, then appointments are sorted chronologically by scheduled time, regardless of appointment type.
Incomplete Appointment Data Handling
Given appointment records missing one or more required fields (time, patient ID, location, clinician), when ingestion occurs, then those records are flagged in error logs, excluded from the queue view, and a notification is generated for data correction.
API Error and Retry Handling
Given an API call that returns an error or times out, when the sync process triggers, then the system retries up to three times with exponential backoff intervals (30s, 60s, 120s) and logs each attempt; if all retries fail, then an alert appears in the dashboard.
Real-Time Unified Queue Display
Given multiple managers viewing the dashboard, when any appointment is added, updated, or removed, then all connected clients automatically refresh their unified queue view within 5 seconds and display identical data sets.
Dynamic Prioritization Engine
"As a clinic manager, I want the system to automatically prioritize appointments based on urgency and clinician availability so that high-priority cases are attended to first."
Description

Implement a rule-based engine that automatically ranks appointments by urgency, clinician availability, patient wait time, and appointment type. Allow configuration of prioritization rules to adapt to clinic policies. The engine recalculates priorities in real time, optimizing clinician utilization and ensuring urgent cases are seen first.

Acceptance Criteria
Urgent Appointment Prioritization
Given there are urgent and non-urgent appointments in the unified queue When the Dynamic Prioritization Engine runs Then all urgent appointments are listed above non-urgent ones
Clinician Availability Adjustment
Given a clinician’s availability changes mid-shift When the engine recalculates priorities Then appointments are reordered to fill the newly available slots without manual intervention
Patient Wait Time Escalation
Given a patient has been waiting beyond the configured threshold When the engine updates rankings Then that patient’s appointment moves to a higher priority position in the queue
Rule Configuration Persistence
Given an admin updates prioritization rules for appointment type weighting When the new rules are saved Then the engine applies the updated rules on all subsequent priority calculations and retains them after a system restart
Real-Time Queue Integrity
Given multiple concurrent updates to appointments While the engine is recalculating priorities Then the queue remains consistent with no lost or duplicated appointments
Real-time Status Updates
"As a clinic manager, I want real-time updates on appointment statuses so that I can monitor patient flow and address delays immediately."
Description

Provide instantaneous status changes (scheduled, checked-in, in session, completed) within the unified queue using WebSocket or push notifications. Ensure any change in appointment status is reflected immediately in the interface. This keeps managers and clinicians informed of patient progress, reducing delays and improving overall flow.

Acceptance Criteria
Status Change Reflection
Given an appointment status is updated to 'checked-in', 'in session', or 'completed', When the backend sends a WebSocket message or push notification, Then the unified queue UI must display the new status within 1 second.
Concurrent Sessions Update
Given multiple appointment statuses change simultaneously, When notifications are received, Then the unified queue must correctly display each appointment's latest status without overwriting or delaying any entry.
Notification Delivery Performance
Given an appointment's status changes, When the system propagates the update, Then the WebSocket or push notification must be delivered with 99% success rate under 500ms latency.
Error Handling for Status Update Failures
Given a failure in delivering a status update to the client, When the client detects the error, Then an error message must display in the UI and the system must retry sending the update up to three times automatically.
Persistent Connection Recovery
Given a WebSocket disconnect occurs, When the connection is re-established, Then the client must automatically fetch any missed status updates and synchronize the unified queue within 2 seconds of reconnection.
Conflict Detection & Resolution
"As a clinic manager, I want the system to detect and suggest resolutions for scheduling conflicts so that I can quickly resolve them without manual checks."
Description

Automatically detect scheduling conflicts such as double bookings, overlapping time slots, or resource contention within the unified queue. Flag conflicts and provide one-click suggestions for alternative slots or clinician reassignments. This feature prevents costly errors and minimizes administrative overhead by streamlining conflict resolution.

Acceptance Criteria
Overlapping Appointment Conflict Detection
Given two appointments for the same clinician with overlapping times exist in the unified queue When the schedule is updated or loaded Then the system highlights both appointments in red And displays a conflict icon next to the clinician’s name And logs the conflict instance in the activity feed
Double Booking Resolution Suggestion
Given a detected conflict due to double booking for a resource When the user clicks the conflict icon Then the system presents at least three alternative time slots without conflicts And allows reassigning the appointment to another qualified clinician with availability
Resource Contention Alert
Given two procedures requiring the same equipment at overlapping times When the unified queue identifies the contention Then the system sends a real-time alert to the practice manager And prevents saving the conflicting appointments until resolved
Automatic Clinician Reassignment Recommendation
Given a scheduling conflict for a clinician When the user triggers the conflict resolution workflow Then the system automatically suggests reassigning the appointment to the next available clinician of the same specialty And updates the queue upon user confirmation
Conflict Resolution Action Tracking
Given a conflict has been resolved When the user confirms the suggested resolution Then the system logs the change with a timestamp and user ID in the audit trail And removes the conflict flag from the appointment
Customizable Queue Filters
"As a clinic manager, I want to filter the unified queue by criteria like appointment type or clinician so that I can focus on relevant appointments."
Description

Enable users to create, apply, and save custom filters on the unified queue by criteria such as date range, appointment type, clinician, or location. Provide an intuitive UI for managing filter profiles. This allows managers to focus on relevant subsets of appointments and improves usability across different operational contexts.

Acceptance Criteria
User Creates and Saves a New Filter Profile
Given the user is on the unified queue screen and selects “Create Filter,” when they define filter criteria (date range, appointment type, clinician, location), name the filter profile, and click “Save,” then the new filter profile appears in the saved filters list and can be selected for future use.
User Applies an Existing Filter to the Queue
Given the user has one or more saved filters, when they select a filter from the saved filters dropdown, then the queue immediately updates to display only the appointments matching the selected filter criteria.
User Edits an Existing Filter Profile
Given the user views their saved filters list, when they choose an existing filter, modify its criteria, and click “Save,” then the filter’s criteria update in the list and applying the filter reflects the new criteria.
User Deletes a Saved Filter Profile
Given the user views their saved filters list, when they select a filter and confirm deletion, then the filter is removed from the list and is no longer available for application.
User Resets to Default Queue View
Given the user has applied one or more filters, when they click “Reset Filters” or select the default view option, then all filters clear and the full, unfiltered queue displays.
User Enters Invalid Filter Criteria
Given the user defines filter criteria with an invalid date range (start date after end date), when they attempt to save or apply the filter, then an inline validation error message displays and prevents saving until the criteria are corrected.
Notification & Alert System
"As a clinic manager, I want to receive alerts when appointments are delayed or overbooked so that I can take corrective action immediately."
Description

Implement a configurable notification system that sends alerts for key queue events (delays, overbookings, clinician check-outs) via email, SMS, or in-app messages. Allow users to set thresholds and delivery channels. This proactive alerting helps managers respond swiftly to issues and maintain smooth clinic operations.

Acceptance Criteria
Delay Threshold Alert Scenario
Given an appointment delay exceeds the user-defined threshold, When the system detects the delay, Then it sends an alert via the configured channel within one minute.
Overbooking Notification Scenario
Given a time slot’s scheduled appointments exceed the maximum configured limit, When overbooking occurs, Then the system sends a notification to the practice manager via email and in-app within two minutes.
Clinician Check-Out Alert Scenario
When a clinician checks out at the end of their shift, Then the system sends an SMS and an in-app message to the clinic manager within one minute.
Notification Channel Configuration Scenario
Given the user selects specific delivery channels (email, SMS, in-app), When the user saves the notification settings, Then all subsequent alerts for configured events are delivered via each selected channel.
Threshold Update Propagation Scenario
When the user updates a notification threshold, Then the new threshold is applied immediately to all future event alerts without requiring a system restart.
Fallback Channel Notification Scenario
Given a primary notification delivery failure, When the system cannot deliver via the primary channel, Then it retries dispatch on a secondary channel within five minutes and logs the failure.

Gap Filler

Automatically detects idle windows in clinicians’ schedules and auto-populates them with waitlisted patients from either virtual or in-office queues. This ensures every available slot is used effectively, maximizing revenue and reducing downtime.

Requirements

Idle Slot Detection Engine
"As a practice manager, I want the system to detect idle appointment windows in clinicians’ schedules automatically so that I can fill them with waitlisted patients and reduce downtime."
Description

Develop an engine that continuously scans clinicians’ schedules in real time to identify unbooked appointment windows, taking into account buffer times, clinician availability, and appointment durations. The engine must integrate with the existing scheduling module, trigger gap detection at configurable intervals, and flag all idle slots exceeding a minimum threshold. This ensures every potential opening is captured for automatic filling, reducing manual oversight and maximizing utilization.

Acceptance Criteria
Detects Unbooked Slots Without Overlaps
Given a clinician’s daily schedule is loaded, when the Idle Slot Detection Engine runs, then it identifies all time windows with no existing appointments or buffer periods and returns a list of start and end times for each idle slot.
Considers Buffer Times in Idle Slot Detection
Given clinician-specific buffer times are configured, when the engine scans the schedule, then it excludes any time windows that fall within those buffer periods from being flagged as idle slots.
Real-Time Gap Detection at Configurable Intervals
Given the gap detection interval is set to a value (e.g., 5 minutes), when the engine runs, then it triggers the detection process automatically at each interval within a tolerance of ±5 seconds and logs each execution timestamp.
Integration with Scheduling Module API
Given an idle slot is detected, when the engine processes it, then it sends a valid API request to the scheduling module containing clinician ID, slot start time, slot end time, and duration without errors or data omissions.
Flags Idle Slots Exceeding Threshold
Given a minimum threshold duration is configured (e.g., 15 minutes), when the engine identifies an idle slot exceeding that threshold, then it marks the slot with a ‘HighPriorityGap’ flag in the system for automatic follow-up.
Waitlist Queue Integration
"As a practice manager, I want the system to automatically pull patients from virtual and in-office waitlists so that every available slot can be offered to waiting patients without manual intervention."
Description

Implement integration with both virtual and in-office waitlists to manage and maintain live queues. The system should pull patient entries, maintain queue order based on wait time and patient priority, and allow synchronization with third-party telehealth and front-desk applications. This ensures the gap filler has immediate access to eligible patients for slot assignment, improving fill accuracy and response time.

Acceptance Criteria
Real-Time Waitlist Synchronization
Given the system is operational and a patient is added or removed from a virtual or in-office waitlist, when the waitlist integration runs, then the waitlist data in Pulseboard updates within 5 seconds, reflecting the addition or removal with accurate timestamps and patient priority.
Priority-Based Queue Ordering
Given multiple patients in the waitlist with varying wait times and priority statuses, when the system processes the queue, then patients are ordered first by priority level (urgent > regular) and then by wait time (longest waited first) without any discrepancies.
Telehealth Application Synchronization
Given a third-party telehealth application is connected via API, when a patient's status changes in the telehealth waitlist (e.g., patient moves from waiting to in-session), then Pulseboard's waitlist reflects this change in real time, with no more than 5 seconds of data latency and proper error handling on API failures.
Front-Desk Application Synchronization
Given the front-desk application records patient check-ins and cancellations, when such events occur, then Pulseboard's waitlist integration ingests and reflects these changes within 5 seconds, maintaining data consistency and retrying up to 3 times on failure, logging errors appropriately.
Idle Slot Patient Assignment
Given an idle appointment slot is detected and there are patients in the integrated waitlist queue, when the gap filler triggers, then the system auto-populates the slot with the next eligible patient, sends confirmation notifications to the patient and clinician within 1 minute, and updates the schedule accordingly, ensuring no slot is double-booked.
Auto-Population Matching Algorithm
"As a practice manager, I want the system to match open appointment slots with the best-suited waitlisted patients so that appointments are filled efficiently and appropriately."
Description

Create a smart matching algorithm that selects the most appropriate waitlisted patient for each detected gap. Criteria should include appointment type compatibility, clinician specialization, patient preferences (location and time), and urgency level. The algorithm must balance equitable distribution among waitlist patients while respecting clinical constraints, ensuring optimal slot utilization and patient satisfaction.

Acceptance Criteria
Notification and Confirmation Workflow
"As a practice manager, I want automated notifications and confirmation requests sent to clinicians and patients when a waitlist‐filled appointment is booked so that everyone is aware of schedule changes and confirmations are tracked."
Description

Design a notification workflow that automatically sends alerts to clinicians and patients when a waitlisted patient is scheduled into an open slot. Notifications should include appointment details, confirmation requests, and rescheduling options. Integrate with email, SMS, and in-app notifications, and handle delivery status and read receipts to confirm that all parties are informed promptly.

Acceptance Criteria
Email Notification to Clinician for Scheduled Waitlisted Patient
Given a waitlisted patient is auto-scheduled into an open slot, When the system sends an email to the clinician, Then the email includes patient name, appointment date/time, location, and confirmation link; And the email is delivered within 1 minute; And the delivery status is recorded as 'Delivered'.
SMS Notification to Patient with Confirmation Request
Given a waitlisted patient’s slot is confirmed, When the system sends an SMS to the patient, Then the SMS contains appointment details, a confirmation link, and rescheduling options; And the SMS is sent within 1 minute; And the delivery status is recorded.
In-App Notification and Read Receipt Logging
Given clinicians and patients have the app open, When a notification arrives, Then it displays appointment details and confirmation actions; And when the recipient views the notification, a read receipt timestamp is logged; And unread notifications persist until viewed.
Notification Delivery Failure and Retry Mechanism
Given a notification fails to send due to network or address errors, When the system detects the failure, Then it retries delivery up to 3 times at 5-minute intervals; And after the final retry, if still failed, an alert is sent to the admin.
Patient Rescheduling Workflow upon Decline
Given a patient declines or ignores the confirmation request, When the system receives the decline or times out after 24 hours, Then the slot is returned to the waitlist queue; And the patient is sent a follow-up notification offering alternative available slots; And the actions are logged.
Gap Filling Analytics Dashboard
"As a practice manager, I want a dashboard showing gap sal-filling metrics and revenue uplift so that I can measure the success of the auto-population feature and make data-driven adjustments."
Description

Build a dashboard module to report on gap-filler performance metrics, including fill rate percentage, average time to fill a gap, additional revenue generated, and clinician utilization improvements. Provide filters for date ranges, clinician views, and facility locations. Display trend charts and exportable reports to help practice managers evaluate the feature’s impact and optimize scheduling strategies.

Acceptance Criteria
Viewing Overall Gap Filling Performance
Given the user navigates to the Gap Filler Dashboard with default settings, when no filters are applied, then the dashboard displays overall fill rate percentage, average time to fill a gap, total additional revenue generated, and clinician utilization improvement metrics, and each metric’s value matches the underlying data for the default period.
Filtering Metrics by Date Range, Clinician, and Location
Given the user sets a custom date range, selects one or more clinicians, and chooses a facility location, when the Apply Filters button is clicked, then the dashboard updates to show only metrics corresponding to the selected parameters, and the number of displayed data points exactly matches the filtered dataset.
Trend Analysis Over Time
Given the user switches to trend chart view, when a custom time interval or preset (e.g., last 7 days, last 30 days) is selected, then the dashboard renders a line or bar chart plotting fill rate percentage and average time to fill gaps over time with correct date labels and data points aligned to the selected interval.
Exporting Reports
Given the user clicks the Export button and chooses CSV or PDF format, when the export process completes, then the generated file downloads automatically and contains all currently visible metrics, applied filter values, and chart data exactly as displayed on the dashboard.
Calculating Additional Revenue and Utilization Improvements
Given the dashboard displays additional revenue and clinician utilization metrics, when metrics are calculated, then additional revenue is correctly summed from fees of filled waitlist slots and clinician utilization improvement percentage is computed based on baseline and current utilization values using predefined formulas and rounding rules.

Waitlist Sync

Continuously synchronizes virtual and in-clinic waitlists in real time. Managers can monitor and manage overflow across channels, ensuring no patient is overlooked and appointment backfills happen seamlessly.

Requirements

Real-Time Waitlist Data Sync
"As a practice manager, I want both virtual and in-clinic waitlists to update instantly in one view so that I can efficiently manage patient flow without missing any appointment requests."
Description

Continuously synchronize and unify the virtual and in-clinic waitlists by pulling real-time data from both channels, merging entries into a single dashboard view, and updating changes within seconds. This ensures managers have an accurate, up-to-the-moment representation of patient queues, reduces the risk of missed appointments, and streamlines oversight by eliminating manual reconciliation.

Acceptance Criteria
Virtual Waitlist Entry Creation
Given the dashboard is active When a new patient is added to the virtual waitlist Then the unified dashboard displays the new entry with patient name, time of request, and status within 2 seconds
In-Clinic Waitlist Entry Update
Given an existing patient on the in-clinic waitlist When the clinic receptionist updates the patient’s status or time on the in-clinic system Then the unified dashboard reflects the updated information within 2 seconds
Simultaneous Additions from Virtual and In-Clinic Channels
Given concurrent waitlist updates When multiple entries are added nearly simultaneously on both virtual and in-clinic systems Then the dashboard merges and orders all entries chronologically without duplicates or omissions within 3 seconds
High-Frequency Updates During Peak Hours
Given peak-hour conditions with 50+ updates per minute When updates occur in rapid succession Then the system processes and displays each update correctly on the unified dashboard without performance degradation
Network Interruption and Recovery
Given a temporary network outage Then the system buffers new waitlist entries locally and, upon reconnection, synchronizes all buffered changes to the dashboard in correct chronological order with no data loss
Overflow Notification Alerts
"As a practice manager, I want to receive notifications when the waitlist exceeds capacity so that I can quickly allocate resources or open new slots to prevent patient backlog."
Description

Implement an alert system that monitors waitlist capacity thresholds for both virtual and clinic queues. When overflow conditions are detected—such as when the waitlist exceeds a predefined limit—trigger configurable notifications via email, SMS, or in-app alerts. This proactive feature helps managers address capacity issues immediately and maintain service quality.

Acceptance Criteria
Clinic Waitlist Threshold Exceeded
Given the clinic waitlist count exceeds the configured threshold, When the overflow condition is detected, Then the system sends an in-app alert to the manager within one minute.
Virtual Waitlist Threshold Exceeded
Given the virtual waitlist count exceeds the configured threshold, When the overflow condition is detected, Then the system sends an SMS notification and an email to the manager within two minutes.
Notification Channel Configuration
Given a manager has selected preferred notification channels in settings, When an overflow condition occurs, Then notifications are sent only via the configured channels (email, SMS, in-app).
Duplicate Notification Prevention
Given an overflow condition persists, When subsequent checks occur within the rate-limit window, Then the system suppresses duplicate notifications to prevent spamming.
Threshold Adjustment Verification
Given a manager updates the overflow threshold value in settings, When the new threshold is saved, Then subsequent overflow detections use the updated threshold for triggering notifications.
Automatic Backfill Prompt Generation
Given an overflow alert is triggered, When the manager views the alert details, Then the system suggests available appointment slots for backfilling from both channels based on priority rules.
Automated Appointment Backfill
"As a scheduler, I want open appointment slots to be filled automatically from the waitlist so that I can reduce idle time and avoid manual rebooking tasks."
Description

Enable automatic backfill of open appointment slots by pulling the next eligible patient from the synchronized waitlist when cancellations or no-shows occur. Allow customization of backfill rules such as patient priority, wait time, and service type to ensure optimal patient matching. This reduces vacant slots, improves clinic utilization, and minimizes administrative overhead.

Acceptance Criteria
Automatic Backfill on Cancellation
Given an appointment slot is vacated due to patient cancellation When the system detects the open slot Then the system automatically selects the next eligible patient from the synchronized waitlist and books them into the available slot
Priority-Based Backfill Rule
Given multiple patients are on the waitlist with varying priority levels When an appointment slot is freed Then the system applies configured priority rules to select the highest priority patient for backfill
Wait Time-Based Backfill Prioritization
Given patients have been waiting for different durations on the waitlist When backfill occurs Then the patient with the longest wait time is chosen for the appointment slot
Service Type Matching for Backfill
Given an open appointment slot is for a specific service type When backfill is triggered Then the system only considers waitlist patients matching the service type before booking
Handling No Eligible Patients in Waitlist
Given an open slot and no patients meet the backfill rules When backfill is attempted Then the system leaves the slot open and notifies the manager that manual assignment is required
Manual Waitlist Adjustment Interface
"As a practice manager, I want to manually adjust the order of waiting patients so that I can accommodate special circumstances and maintain control over appointment priorities."
Description

Provide a dedicated interface within the dashboard for practice managers to manually add, remove, or reprioritize patients across virtual and clinic waitlists. Include drag-and-drop functionality, bulk operations, and audit entries to support quick adjustments and overrides while maintaining data integrity and traceability.

Acceptance Criteria
Single Patient Drag-and-Drop Adjustment
Given a patient is listed on the virtual waitlist and the manager is on the Manual Waitlist Adjustment Interface, when the manager drags the patient to the clinic waitlist and drops them at a specific position, then the patient is removed from the virtual waitlist, appears at the dropped position on the clinic waitlist, and a success notification is displayed.
Bulk Patient Reprioritization
Given the manager has selected multiple patients on a waitlist, when the manager drags the selection to a new position or uses the bulk reprioritize option, then all selected patients are reordered accordingly, the updated positions are reflected on both waitlists, and a summary update is displayed.
Patient Removal from Waitlist
Given a patient is on either the virtual or clinic waitlist, when the manager selects the patient and confirms removal through the remove action, then the patient is removed from the waitlist, the total count updates, and a confirmation message is shown.
Audit Log Entry Creation
Given any manual adjustment (add, remove, or reprioritize) is performed, when the action completes, then an audit entry with patient ID, action type, original and new positions, timestamp, and manager ID is recorded and viewable in the audit log.
Real-Time Synchronization Verification
Given a manual adjustment is made on one client session, when another manager views the Manual Waitlist Adjustment Interface within five seconds, then the updated waitlist state matching the first session is displayed without requiring a page refresh.
Waitlist Audit Logging
"As an administrator, I want to review an audit log of all waitlist changes so that I can ensure compliance and investigate any discrepancies in patient scheduling."
Description

Maintain a detailed audit log of all waitlist synchronization events and manual adjustments, capturing timestamps, user actions, and source channels (virtual or in-clinic). Provide filterable and exportable logs within the dashboard for compliance, troubleshooting, and performance review, ensuring full transparency of patient flow operations.

Acceptance Criteria
Real-time Synchronization Event Logging
Given a waitlist synchronization event occurs between virtual and in-clinic channels When the event completes Then an audit log entry is created containing the event timestamp, user ID (system or user), event type ('sync_complete'), and source channel
Manual Waitlist Adjustment Logging
Given a user manually adjusts a patient's position or moves them between virtual and in-clinic waitlists When the adjustment is saved Then an audit log entry is created capturing the timestamp, user ID, action performed, and source and destination channels
Filtering Audit Logs by Date and Channel
Given the user accesses the audit logs and applies filters for a specific date range and channel When the filter is applied Then only log entries within the date range and from the selected channel are displayed
Exporting Filtered Audit Logs
Given the logs are filtered by criteria When the user clicks 'Export CSV' Then a CSV file is generated within 5 seconds containing only the filtered entries with all audit fields
Viewing Audit Log Entry Details
Given the user has the audit logs displayed When the user selects a specific log entry Then the system displays a detailed view showing all captured fields including timestamp, user action, source channel, and patient identifier

PriorityBalancer

Dynamically reorders appointments based on urgency, patient preferences, and clinician expertise. This adaptive system ensures critical cases receive timely attention while balancing demand across virtual and in-person sessions.

Requirements

Real-Time Priority Calculation
"As a practice manager, I want the system to recalculate appointment priorities in real time so that critical cases are handled promptly and resources are used efficiently."
Description

The system must calculate appointment priorities in real time, assessing factors like case severity, wait time, and resource availability to dynamically reorder the schedule. This functionality ensures high-urgency cases are surfaced immediately, reducing patient risk and optimizing clinician workload. It integrates with the existing scheduling engine and data feeds, updating the dashboard within seconds of new information.

Acceptance Criteria
Surge in Critical Cases
Given a new appointment with case severity marked as critical, When the appointment is entered into the system, Then the system recalculates priorities and surfaces the critical appointment at the top of the schedule within 2 seconds.
Wait Time Escalation Adjustment
Given an appointment has exceeded its defined wait-time threshold, When the current time surpasses the threshold, Then the system automatically increases the appointment’s priority level and reorders the schedule accordingly.
Resource Unavailability Handling
Given a clinician becomes unavailable mid-shift, When the system detects the unavailability through the resource feed, Then all affected appointments are immediately reprioritized and reassigned within 3 seconds.
Integration Latency Verification
Given real-time data feeds (severity, wait time, resource status) are updated, When the scheduler runs its priority calculation, Then the dashboard reflects the updated appointment order within 3 seconds with no data discrepancies.
Patient Preference Respect
Given a patient has specified a preference for clinician expertise, When multiple high-urgency appointments are prioritized, Then the system honors the preference without delaying critical cases and logs any trade-offs made.
Clinician Expertise Weighting
"As a practice manager, I want appointment priorities to consider clinician expertise so that patients receive care from the most appropriate providers."
Description

Incorporate clinician profiles and expertise levels into the prioritization algorithm by weighting appointments based on clinician specialty, certifications, and past performance. This ensures patients are matched with the most qualified providers, improving outcomes and reducing misallocations. It integrates with the clinician database and performance metrics to dynamically adjust priority scores.

Acceptance Criteria
Urgent Case Routed to Highest Expertise Clinician
Given an appointment marked as 'high urgency' and multiple available clinicians, when the priority algorithm executes, then the appointment is assigned to the clinician with the highest combined expertise weight score.
Scheduling Adjustment After Certification Update
Given a clinician's certification is added to their profile, when the priority algorithm recalculates next day's schedule, then appointments requiring that certification are reprioritized to favor that clinician over others lacking that certification.
Dynamic Reprioritization Following Performance Improvement
Given a clinician's performance metrics improve by at least 10% in quality score, when the system updates performance scores, then future appointment assignments reflect the new higher priority weighting for that clinician.
Assignment When New Clinician Onboarded
Given a newly onboarded clinician with specified specialties and certifications, when their profile is added to the clinician database, then upcoming relevant appointments are reevaluated and assigned to include this clinician based on matching expertise.
Balancing In-Person and Virtual Demand with Expertise Weighting
Given simultaneous in-person and virtual appointment requests with similar urgency, when scheduling occurs, then appointments are distributed to clinicians to balance modality demand while still assigning to the most qualified clinicians based on expertise weight.
Patient Preference Integration
"As a patient, I want my scheduling preferences to be considered so that appointments fit my availability and modality needs."
Description

Capture and integrate patient preferences—such as preferred appointment times, virtual vs. in-person modality, and clinician language skills—into the prioritization logic. The system respects these preferences while balancing clinical urgency, enhancing patient satisfaction and adherence. It connects with the patient portal and preference settings interface to fetch and apply these details.

Acceptance Criteria
Capture Patient Preference on Booking
Given a patient selects appointment preferences (date/time, modality, clinician language) in the portal, When the booking is submitted, Then the system stores all selected preferences in the appointment record.
Integrate Preferences into Prioritization Logic
Given multiple pending appointments, When the prioritization algorithm runs, Then appointments are ranked incorporating patient preferences alongside clinical urgency and clinician expertise.
Real-time Preference Updates
Given a patient updates their appointment preferences in the portal, When the changes are saved, Then the system fetches and applies the updated preferences to the existing appointment queue within 5 minutes.
Language Skill Matching
Given a patient preference for a specific clinician language, When scheduling or reordering appointments, Then only clinicians with matching language skills are assigned, or an alert is generated if none available.
Preference Override Notification
Given a critical urgency case conflicts with a patient's modality preference, When the system overrides the patient preference, Then a notification is sent to the patient explaining the change and offering rescheduling options.
Urgency Threshold Alerts
"As a clinician, I want to receive alerts when urgent cases approach critical wait times so that I can intervene promptly."
Description

Define configurable urgency thresholds that trigger alerts when a case exceeds a predefined wait time or severity score. The system notifies practice managers and clinicians via the dashboard and optional email/SMS, prompting immediate intervention. This proactive alerting prevents critical delays and enhances patient safety by ensuring urgent cases are escalated.

Acceptance Criteria
Threshold Exceeded for Wait Time
Given the admin has set the maximum wait time threshold to 30 minutes, when a patient's wait time exceeds 30 minutes, then an alert must appear on the dashboard within 1 minute.
Severity Score Surpassed Configuration
Given the clinician assigns a severity score above the configured threshold of 8, when the record is saved, then an alert must be generated on the dashboard immediately.
Dashboard and Email/SMS Notification Delivery
Given notification channels (email and SMS) are enabled for practice managers and clinicians, when an alert is triggered, then email and SMS notifications containing patient ID, severity score, and wait time must be sent to all designated recipients within 2 minutes.
User Acknowledgment and Alert Clearance
Given an active alert is displayed on the dashboard, when a practice manager clicks the ‘Acknowledge’ button, then the alert status must change to ‘Acknowledged’ and the visual notification badge must clear from the dashboard.
Audit Logging of Alert Events
Given an alert is triggered, when the system logs the event, then the audit log must include timestamp, patient ID, threshold type, configured threshold value, actual measured value, and user acknowledgment details.
Balanced Appointment Queue
"As a practice manager, I want the system to balance appointment types so that both in-person and virtual slots are utilized effectively."
Description

Ensure equitable distribution of appointments across in-person and virtual sessions by enforcing balance constraints within the scheduling algorithm. The system prevents overbooking in one channel while underutilizing another, optimizing resource utilization and patient throughput. It integrates with both session management modules and provides real-time queue analytics.

Acceptance Criteria
Initial Load Balance Check
Given the system loads the day’s appointments from both in-person and virtual modules, when the scheduling algorithm initializes, then the total number of appointments per channel must not differ by more than 10%.
Dynamic Rebalancing Post-Cancellation
Given a cancellation in either channel, when the system recalculates the queue, then appointments are shifted to ensure neither channel exceeds a 15% imbalance threshold.
Real-Time Queue Analytics Display
Given an active scheduling dashboard, when a user views queue analytics, then the displayed in-person and virtual appointment counts and imbalance percentage are updated within two seconds of any change.
Peak Hour Appointment Distribution
Given scheduling requests during identified peak hours, when new bookings are made, then the system enforces a maximum of 50% of total appointments in one channel for that hour.
Urgent Case Prioritization
Given an appointment marked as urgent, when it is added to the queue, then the system elevates its position but still maintains overall channel balance within the defined 15% tolerance.

ChannelSwap Assistant

Enables instant conversion of appointment modalities to match real-time needs. Staff can switch slots between virtual and in-office formats with one click, quickly adapting to changing patient flow and maximizing schedule efficiency.

Requirements

Instant Modality Switch
"As a clinic staff member, I want to switch an appointment between virtual and in-office formats with a single click so that I can quickly adapt to last-minute changes and maintain schedule efficiency."
Description

Implement a one-click control within the Pulseboard dashboard that enables staff to seamlessly convert an appointment’s modality from in-office to virtual or vice versa. This feature should instantly update the scheduling system, reflect changes in real time across all user interfaces, and ensure that billing codes and resource allocations adjust accordingly. By minimizing manual steps and eliminating delays, the requirement enhances operational flexibility and helps optimize clinician time utilization.

Acceptance Criteria
One-Click Modality Toggle
Given an appointment is scheduled as in-office When a staff member clicks the 'Switch Modality' button Then the appointment modality updates to virtual in the scheduling system within 2 seconds
Real-Time Dashboard Sync
Given the modality is switched When the change is made Then the updated appointment view must propagate to all active user interfaces within 3 seconds without requiring a refresh
Automated Billing Code Update
Given an appointment modality change occurs When the switch is confirmed Then the billing code must automatically update to the correct code for the new modality and flag any discrepancies for review
Dynamic Resource Reallocation
Given a modality switch to in-office When the change is processed Then room assignments and staff schedules must reallocate automatically and display the updated resource availability in the dashboard
Concurrent Modality Change Handling
Given two staff members attempt to switch the same appointment modality simultaneously When the second request is received Then the system must queue or reject the second action with an error message indicating the change is in progress
Schedule Conflict Detection
"As a practice manager, I want the system to notify me of any scheduling conflicts when I change an appointment’s modality so that I can resolve issues proactively and avoid double-bookings."
Description

Incorporate a conflict detection engine that automatically checks for time overlaps, room availability, and provider assignment before confirming any modality switch. The system should alert users of potential conflicts and offer resolution suggestions, such as alternative slots or providers. This requirement ensures that switching modalities does not introduce scheduling errors and maintains the integrity of patient flow.

Acceptance Criteria
Overlapping Appointment Detection
Given a user requests a modality switch to a time slot that overlaps with another appointment, When the system validates the schedule, Then the system blocks the switch and displays an overlapping appointment error.
Room Availability Check
Given a user requests a modality switch to an in-office appointment, When no rooms are available at the selected time, Then the system alerts the user of room unavailability.
Provider Availability Check
Given a user requests a modality switch at a time when the assigned provider is unavailable, When the system checks the provider’s schedule, Then the system notifies the user of provider unavailability.
Conflict Alert Display
Given a detected conflict during a modality switch, When the system runs conflict detection, Then the system displays a clear alert specifying the conflict type.
Alternative Slot Suggestion
Given a detected scheduling conflict, When the system cannot complete the requested switch, Then the system offers at least three alternative available time slots.
Alternative Provider Suggestion
Given a provider unavailability conflict, When the system identifies no open slots with the current provider, Then the system suggests at least two qualified alternative providers.
Successful Switch Confirmation
Given no scheduling conflicts are detected during a modality switch, When the system processes the change, Then the system confirms the switch and updates the appointment record.
Automated Patient Communication
"As a receptionist, I want patients to receive immediate notifications when I alter their appointment format so that they are aware of changes without requiring manual outreach."
Description

Develop an automated notification module that sends real-time updates to patients whenever their appointment modality changes. Notifications should be delivered via SMS, email, or in-app message based on patient preferences, clearly indicating the updated modality, instructions for virtual visits (e.g., video link), or check-in procedures for in-person visits. This feature reduces no-shows and enhances patient engagement by keeping them informed.

Acceptance Criteria
Patient Preference-Based Notification Delivery
Given a patient has specified SMS as their communication preference, when the appointment modality is changed, then the system must send an SMS notification within one minute of the change.
Virtual Visit Instruction Inclusion
Given an appointment is switched to virtual, when the notification is generated, then the message must include a working video link and step-by-step login instructions.
In-Person Check-In Procedure Notification
Given an appointment is switched to in-person, when the notification is sent, then it must include the clinic address, check-in desk number, and parking directions.
Handling Undeliverable Notifications
Given an SMS notification fails to deliver, when the first attempt fails, then the system retries delivery twice and, upon final failure, sends the notification via the patient's secondary preference.
Real-Time Notification Performance
Given a modality change event occurs, when the change is confirmed in the system, then the notification status in the dashboard updates to 'Sent' within 30 seconds.
Real-Time Capacity Visualization
"As a scheduler, I want to see current availability for virtual and in-person sessions on a single screen so that I can allocate appointments where capacity exists and avoid bottlenecks."
Description

Provide a visual dashboard component that displays real-time capacity metrics for both virtual and in-office appointments. The view should show available slots, occupied rooms, and provider schedules, updating dynamically after every modality switch. By offering at-a-glance insights into resource utilization, this requirement helps staff make informed decisions when reallocating appointments and prevents overbooking.

Acceptance Criteria
Modality Switch Updates Capacity Dashboard
Given an existing in-office appointment When the staff uses ChannelSwap Assistant to convert it to virtual Then the dashboard updates within 2 seconds to decrease occupied rooms by one and increase virtual slot availability by one
Room Availability Change on Swap
Given all rooms are occupied When a virtual appointment is switched to in-office Then the dashboard displays an overbooking warning and highlights available rooms or suggests rescheduling options
Provider Schedule Reflection After Swap
Given a provider has back-to-back appointments When one appointment’s modality is swapped Then the provider’s schedule view reflects updated appointment type and resource allocation without overlapping slots
Real-Time Slot Availability During Peak Hours
Given peak operation hours with multiple appointment swaps occurring When three or more swaps are processed consecutively Then the capacity view refreshes in real time without lag and accurately shows available vs occupied slots
Concurrent Swaps Without Data Mismatch
Given two staff members swap different appointments simultaneously When swaps complete Then the dashboard shows correct total counts for virtual and in-office slots with no data inconsistencies
Swap Audit Logging
"As a clinic administrator, I want to track every appointment modality change in an audit log so that I can review swap history for compliance and operational insights."
Description

Implement comprehensive audit logging for every modality swap action, capturing details such as the user performing the change, timestamp, original modality, new modality, and reason for the switch if provided. Logs should be stored securely, searchable, and downloadable for compliance and reporting purposes. This requirement ensures accountability, supports regulatory audits, and enables performance analysis.

Acceptance Criteria
Audit Entry Creation on Modality Swap
Given a user swaps appointment modality, when the swap is confirmed, then a log entry must be created containing user ID, timestamp, original modality, new modality, and reason if provided.
Secure Storage of Audit Logs
Given an audit entry is created, then it must be written to an encrypted audit log database with access controls preventing unauthorized read/write operations.
Search and Filter Audit Records
Given audit logs exist, when an admin applies filters by date range, user ID, or modality change, then the system returns matching entries within two seconds sorted by timestamp descending.
Downloadable Audit Log Export
Given filtered audit results, when an admin clicks Export, then the system generates a CSV file including all fields and initiates a browser download within five seconds.
Optional Reason Capture Validation
Given a user performs a modality swap without entering a reason, when the swap is saved, then the reason field in the audit log entry must be empty but present, and when a reason is provided, it must match the entered text.

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Pulseboard Launches AI-Driven Predictive Pulse to Preempt Clinic Bottlenecks

Imagined Press Article

CHICAGO, IL — 2025-06-11 — Pulseboard today announced the release of Predictive Pulse, an AI-powered forecasting engine designed to anticipate and resolve clinic workflow challenges before they occur. Built on advanced machine learning algorithms trained on historical and real-time data from hundreds of small practices, Predictive Pulse delivers actionable insights that empower practice managers to allocate resources proactively, minimize patient wait times and sustain operational efficiency throughout every shift. In today’s fast-paced outpatient environment, clinic managers face mounting pressures to reduce bottlenecks, maintain high patient satisfaction and keep overhead costs in check. Traditional reactive tools only signal issues once they have already impacted patient flow, leaving staff scrambling to make adjustments on the fly. With Predictive Pulse, managers gain a forward-looking view into potential pinch points—identifying scheduling gaps, staffing shortages or room occupancy spikes up to two hours in advance. “Predictive Pulse represents a paradigm shift in clinic operations,” said Elena Martinez, Chief Product Officer at Pulseboard. “By harnessing the power of AI and real-time analytics, we’re giving small practice managers the ability to see around corners. Instead of firefighting through the day, they can proactively fine-tune schedules, reassign staff and reconfigure resources to avoid disruptions before they happen.” Key benefits of Predictive Pulse include: • Early Warning Alerts: Automated notifications are delivered via the Pulseboard dashboard and SMS when predicted wait times or room occupancy exceed custom thresholds, enabling immediate intervention. • Dynamic Staffing Recommendations: The platform suggests optimal staff assignments based on forecasted patient volume, clinician specialties and historical performance metrics. • Scenario Modeling: Practice managers can simulate “what-if” scenarios—such as adding or removing appointments, shifting staff schedules or reallocating exam rooms—to evaluate the impact on patient flow and resource utilization. • Visual Heatmaps: Interactive, color-coded layouts illustrate projected congestion zones in waiting areas and exam rooms, guiding timely adjustments to staff deployment. Early adopters of Predictive Pulse have already reported significant improvements in operational performance. Brightway Pediatrics, a two-physician practice in Chicago, reduced average patient wait times by 18% within the first month of deployment. “We’ve gone from constantly juggling last-minute schedule changes to running our clinic like clockwork,” said Sarah Klein, Practice Manager at Brightway Pediatrics. “Predictive Pulse tells me where the pressure points will be and gives me the confidence to move resources proactively. Our patients are happier, our staff is less stressed, and we’re maximizing throughput every day.” Pulseboard continues to integrate Predictive Pulse seamlessly with its unified dashboard, which merges scheduling, billing and patient flow tracking into one intuitive interface. This holistic approach ensures that practice managers can address both operational and financial performance in tandem—anticipating workflow issues that could lead to billing delays or claim errors. “As small practices navigate evolving patient expectations and regulatory requirements, they need tools that simplify complexity rather than add to it,” said Martinez. “Predictive Pulse not only predicts potential workflow disruptions but also aligns those predictions with billing and resource utilization data. The net result is a calmer clinic environment, faster reimbursements and measurable cost savings.” Availability and Pricing Predictive Pulse is immediately available to all Pulseboard subscribers at no additional cost through June 2025. After the introductory period, standalone pricing will begin at $49 per month per clinic location, with volume discounts available for multi-site practices. About Pulseboard Pulseboard is the leading unified clinic management platform for small practice managers. By merging scheduling, billing and patient flow into one real-time dashboard, Pulseboard empowers clinics to reduce administrative burdens, prevent costly errors and improve both patient and staff satisfaction. Trusted by thousands of providers nationwide, Pulseboard is committed to delivering innovative, user-friendly solutions that restore calm and control to every shift. Media Contact: Linda Harper Director of Communications, Pulseboard lharper@pulseboard.com (312) 555-0147

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Pulseboard Introduces Claim Preflight to Revolutionize Billing Accuracy and Accelerate Revenue

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NEW YORK, NY — 2025-06-11 — Pulseboard today unveiled Claim Preflight, a breakthrough feature that simulates insurance claim submissions before they go live, predicting acceptance likelihood and flagging potential denials. By providing an early-warning system for common billing pitfalls, Claim Preflight helps small practices reduce rejections, shorten revenue cycles and optimize financial performance without adding complexity to existing workflows. Billing departments in small clinics often grapple with high claim denial rates—often exceeding 12%—which can translate into thousands of dollars in lost revenue and months of follow-up work. Traditional post-submission denial management consumes valuable staff hours and delays reimbursements, negatively impacting cash flow. Claim Preflight flips the script by evaluating each claim against payer-specific rules, fee schedules and policy nuances before submission, giving billing professionals the opportunity to address errors proactively. “Claim Preflight is like having a virtual billing auditor at your fingertips,” said Ravi Patel, Vice President of Product Development at Pulseboard. “Our system runs each claim through a simulation of payer adjudication logic, complete with real-time policy updates, so you can correct issues before they ever leave your office. Practices can realize immediate improvements in first-pass acceptance rates and free up staff to focus on strategic initiatives rather than manual scrubbing.” Highlights of Claim Preflight include: • Real-Time Denial Predictions: Each claim is scored on an acceptance probability and accompanied by a detailed report of flagged issues, such as invalid codes, missing modifiers or documentation gaps. • Interactive Correction Guidance: Claim Preflight offers step-by-step recommendations for resolving errors, with links to relevant policy references and coding rationale. • Payer Policy Integration: The module continuously ingests updates from major commercial and government payers, ensuring claims adhere to the latest coverage rules and bundling restrictions. • Batch Preflight Mode: Large practices can upload entire claim batches for simultaneous simulation, streamlining high-volume workflows and prioritizing the most urgent fixes. Early validation of Claim Preflight at Northside Family Clinic in Atlanta demonstrated a 32% reduction in denials during the first 60 days of use. “We’ve never seen our denial rate drop so dramatically,” said Angela Brooks, Billing Manager at Northside Family Clinic. “Claim Preflight not only tells us what’s wrong but shows us exactly how to fix it. Our team is more confident, claim turnaround is faster, and our revenue has never been healthier.” Pulseboard’s unified dashboard ensures that Claim Preflight insights are integrated with scheduling and patient flow data, equipping managers with a comprehensive view of both operational and financial health. With centralized visibility into appointment volumes, procedure codes and payer mixes, practice leaders can make informed decisions that balance patient access with revenue objectives. “Integrating operational and billing intelligence is the cornerstone of Pulseboard’s mission,” said Patel. “By bridging the gap between front-end scheduling and back-end revenue operations, we’re delivering a truly end-to-end solution that optimizes efficiency at every stage of the patient journey.” Availability and Pricing Claim Preflight is available immediately as part of Pulseboard’s Advanced Billing Suite, starting at $99 per month per clinic location. Practices with multiple sites qualify for tiered discounts. A 30-day free trial is offered for new subscribers. About Pulseboard Pulseboard is the all-in-one clinic management platform purpose-built for small practice managers. From scheduling and patient flow to billing and revenue optimization, Pulseboard provides real-time visibility and intelligent automation to streamline operations, reduce errors and enhance the patient experience. Media Contact: Marcus Chen Head of Healthcare Communications, Pulseboard mchen@pulseboard.com (646) 555-0273

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Pulseboard Debuts Onboard Orbit Interactive Training Suite to Expedite Staff Adoption

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SAN FRANCISCO, CA — 2025-06-11 — Pulseboard today launched Onboard Orbit, an immersive training suite designed to accelerate new user adoption and boost proficiency across clinic teams. Combining interactive simulations, gamified checkpoints and AI-driven coaching, Onboard Orbit transforms onboarding from a time-consuming task into an engaging, results-driven experience that reduces learning curves by up to 50%. Small practices transitioning from manual or legacy systems often struggle with staff resistance, inconsistent training outcomes and productivity dips as employees grapple with unfamiliar software. Onboard Orbit addresses these challenges head-on by delivering a structured, modular learning journey that adapts to each user’s role, pace and skill level. “Successful software adoption is not just about features—it’s about people,” said Allison Rivera, Head of Customer Success at Pulseboard. “Onboard Orbit is the culmination of years of feedback from clinic managers who told us they needed a training solution that was intuitive, measurable and fun. By embedding lessons in realistic scenarios and reinforcing key concepts through gamification, we’re seeing teams ramp up faster, make fewer mistakes and feel confident in their day-to-day workflows.” Core components of Onboard Orbit include: • Scenario Simulator: Realistic, hands-on simulations guide new hires through common scheduling, billing and patient flow tasks, providing a risk-free environment to practice and master essential functions. • Checkpoint Challenges: Short, interactive quizzes and tasks at critical milestones reinforce learning and ensure comprehension before progressing to the next module. • Virtual Coach Chat: An AI-powered assistant offers on-demand guidance, best-practice tips and instant feedback, reducing downtime when users encounter questions or obstacles. • Progress Dashboard: Managers can monitor individual and team-level training metrics, track module completion rates, identify knowledge gaps and celebrate milestones with digital badges. • Shadow Scheduler Integration: New hires can schedule live shadowing sessions with experienced staff directly within the platform, ensuring hands-on mentorship and real-world context. Early pilot programs revealed impressive results: Sunnyvale Family Practice reduced new user training time by 47% and reported a 92% satisfaction rate with the onboarding process. “Onboard Orbit changed the game for us,” said Priya Desai, Clinic Operations Lead at Sunnyvale Family Practice. “Our staff loved the interactive approach—especially the virtual coach—and we saw fewer support tickets in the first month. It’s a win-win for our team and our bottom line.” By embedding Onboard Orbit into the core Pulseboard platform, practice managers benefit from seamless integration between training and daily operations. Learning modules can be customized to align with specific clinic workflows, and completion badges automatically unlock system permissions, ensuring new users have access to the right features at the right time. “We believe training should be an ongoing journey, not a one-time event,” said Rivera. “Onboard Orbit lays the foundation for continuous learning, equipping teams to adapt quickly to new features, regulatory updates and evolving best practices.” Availability and Pricing Onboard Orbit is available immediately as an add-on to Pulseboard’s Enterprise package, priced at $79 per user per month. Organizations with more than 25 users qualify for volume-based discounts and bespoke implementation support. About Pulseboard Pulseboard is the unified clinic management solution that brings scheduling, billing and patient flow into a single, real-time dashboard. Designed for small practices and clinic managers, Pulseboard’s intelligent automation and analytics tools reduce administrative overhead, prevent errors and elevate the patient and staff experience. Media Contact: Rachel Nguyen Senior PR Manager, Pulseboard rnguyen@pulseboard.com (415) 555-0389

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