Intelligent Medical Scheduling MVP Development
Budget: $3,000 – $5,000 USD
Web-Based MVP: Intelligent Scheduling & Workload Prediction System for Medical Facility
We are looking for an experienced freelancer or small development team to build a web-based MVP (Minimum Viable Product) of an intelligent scheduling and operational support system for a large medical network.
The goal of this project is to develop a fully functional, browser-based demonstrator that operates on synthetic (simulated) data and showcases how the system would support scheduling, staffing decisions, and workload prediction in a real healthcare environment.
This is not a production-level enterprise system — it is an MVP intended for demonstrations, stakeholder discussions, and preparation for a future pilot deployment.
⸻
Scope of the MVP (web-based application)
The MVP should be delivered as a working web application, accessible online, with a simple UI and clear user flow.
The system should include the following functional areas (in simplified form):
⸻
1) Doctor / staff scheduling module
• calendar / timetable view
• staffing coverage by time slots / shifts
• conflict detection, including:
• understaffed time periods
• scheduling conflicts / shift overlaps
• exceeding working hour limits
• manual editing / adjustments in the schedule
⸻
2) Automatic suggestions & recommendations (rule-based / heuristic logic)
The MVP should generate system suggestions such as:
• recommended shift swaps
• suggested reassignment of staff between units
• flagged risk areas in the schedule
Examples:
• “Suggested shift swap between staff A and B”
• “Recommended reassignment to cover high-priority workload”
• “Minimum staffing not met — additional coverage required”
AI / ML is not required at this stage — simple rule-based or heuristic logic is sufficient, as long as the system behavior is consistent and realistic.
⸻
3) Basic workload prediction (simplified MVP version)
A simplified workload indicator, such as:
• low / medium / high workload risk
Displayed in the schedule or dashboard, with a short explanation (e.g. “increased visit concentration between 10:00–12:00”).
This may be implemented using:
• moving averages,
• simple statistical logic,
• heuristic thresholds.
⸻
4) “What-if” simulation panel
Example scenarios to support:
• absence of a staff member during selected hours
• sudden increase in patient volume (e.g. +20%)
The system should:
• highlight risk zones,
• show where coverage is insufficient,
• present recommended adjustments or reallocations.
⸻
5) Alerts & notifications (inside the web panel)
Including (simplified):
• missing coverage / staffing gaps
• overtime / excessive workload indicators
• conflicting shifts
• high-risk workload periods
⸻
6) Synthetic data — realistic & scenario-based
The MVP should operate on synthetic test data, but the data must reflect realistic operational conditions, such as:
• multiple departments / clinics
• different shift patterns
• night / weekend coverage
• absence / unavailability cases
• workload fluctuations
Synthetic datasets may be prepared collaboratively.
⸻
Technical expectations
Preferred (but not strictly required) approach:
Backend / logic:
• Python OR similar
• rule-based / heuristic decision logic
• optional solver frameworks (e.g. OR-Tools)
Data layer:
• simple database or structured data storage
Frontend / delivery:
• web-based dashboard / application
• accessible from browser (no desktop installation)
The final MVP must be delivered as:
a working, online, web-based application ready for live demonstration
(not just code or mock-ups).
⸻
Delivery expectations
The deliverable should include:
• functioning web application hosted in a demo environment
• access for presentation and testing purposes
• ability to run predefined demonstration scenarios
• brief technical handover / instructions
We value:
• clean, pragmatic implementation,
• focus on usability and clear scenario presentation,
• experience with MVPs, PoC systems or decision-support tools.
We are looking for an experienced freelancer or small development team to build a web-based MVP (Minimum Viable Product) of an intelligent scheduling and operational support system for a large medical network.
The goal of this project is to develop a fully functional, browser-based demonstrator that operates on synthetic (simulated) data and showcases how the system would support scheduling, staffing decisions, and workload prediction in a real healthcare environment.
This is not a production-level enterprise system — it is an MVP intended for demonstrations, stakeholder discussions, and preparation for a future pilot deployment.
⸻
Scope of the MVP (web-based application)
The MVP should be delivered as a working web application, accessible online, with a simple UI and clear user flow.
The system should include the following functional areas (in simplified form):
⸻
1) Doctor / staff scheduling module
• calendar / timetable view
• staffing coverage by time slots / shifts
• conflict detection, including:
• understaffed time periods
• scheduling conflicts / shift overlaps
• exceeding working hour limits
• manual editing / adjustments in the schedule
⸻
2) Automatic suggestions & recommendations (rule-based / heuristic logic)
The MVP should generate system suggestions such as:
• recommended shift swaps
• suggested reassignment of staff between units
• flagged risk areas in the schedule
Examples:
• “Suggested shift swap between staff A and B”
• “Recommended reassignment to cover high-priority workload”
• “Minimum staffing not met — additional coverage required”
AI / ML is not required at this stage — simple rule-based or heuristic logic is sufficient, as long as the system behavior is consistent and realistic.
⸻
3) Basic workload prediction (simplified MVP version)
A simplified workload indicator, such as:
• low / medium / high workload risk
Displayed in the schedule or dashboard, with a short explanation (e.g. “increased visit concentration between 10:00–12:00”).
This may be implemented using:
• moving averages,
• simple statistical logic,
• heuristic thresholds.
⸻
4) “What-if” simulation panel
Example scenarios to support:
• absence of a staff member during selected hours
• sudden increase in patient volume (e.g. +20%)
The system should:
• highlight risk zones,
• show where coverage is insufficient,
• present recommended adjustments or reallocations.
⸻
5) Alerts & notifications (inside the web panel)
Including (simplified):
• missing coverage / staffing gaps
• overtime / excessive workload indicators
• conflicting shifts
• high-risk workload periods
⸻
6) Synthetic data — realistic & scenario-based
The MVP should operate on synthetic test data, but the data must reflect realistic operational conditions, such as:
• multiple departments / clinics
• different shift patterns
• night / weekend coverage
• absence / unavailability cases
• workload fluctuations
Synthetic datasets may be prepared collaboratively.
⸻
Technical expectations
Preferred (but not strictly required) approach:
Backend / logic:
• Python OR similar
• rule-based / heuristic decision logic
• optional solver frameworks (e.g. OR-Tools)
Data layer:
• simple database or structured data storage
Frontend / delivery:
• web-based dashboard / application
• accessible from browser (no desktop installation)
The final MVP must be delivered as:
a working, online, web-based application ready for live demonstration
(not just code or mock-ups).
⸻
Delivery expectations
The deliverable should include:
• functioning web application hosted in a demo environment
• access for presentation and testing purposes
• ability to run predefined demonstration scenarios
• brief technical handover / instructions
We value:
• clean, pragmatic implementation,
• focus on usability and clear scenario presentation,
• experience with MVPs, PoC systems or decision-support tools.