Pharmacy Safety System

Status: Functional prototype with full system design documentation
Goal: Reduce pharmacy dispensing errors by providing an automated prescription validation and decision-support tool.

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Overview

The Pharmacy Safety System is a Flask-based prototype web application backed by detailed system design and modeling.
It supports pharmacists by automatically validating prescriptions against multiple safety and compliance checks, helping to reduce risks of:

• Drug interactions
• Duplicate dosages
• Invalid or fraudulent prescriptions
• Insurance and identity mismatches
• Regulatory alerts and shortages

The system provides pharmacists with clear decision support while maintaining final control over approval.

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Features

• Prescription Workflow

  • View pending, in-progress, and completed prescriptions
  • Process prescriptions step by step with automated checks

• Automated Validation

  • Patient insurance verification
  • Physician credential validation
  • Inventory and stock availability check
  • Drug interaction and safety alerts
  • Regulatory alerts (e.g., shortages, outbreak-related demand)
  • Patient medical history and allergy checks

• Decision Support Dashboard

  • Displays results of each check (green = safe, yellow = caution, red = critical)
  • Allows pharmacists to approve, reject, or override with comments

• Audit & Logging

  • Every decision is logged for traceability and accountability

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Architecture & Design

This project was initially developed as a software architecture case study and extended into a working prototype.
It includes full design documentation:

• Data Flow Diagrams (DFD) – Level 1–3 decomposition of the prescription process
• Entity & Data Dictionaries – Six interconnected databases:
  • Drug Inventory
  • Prescription History
  • Drug Interactions
  • Patient Records
  • Order Analytics
  • Electronic Prescriptions
• Use Case Diagrams & Pseudocode – Detailed workflows for validation, doctor verification, conflict resolution
• UML & Sequence Diagrams – Modeling system logic and interactions
• Prototype Implementation – Flask web app, SQLite backend, Bootstrap frontend

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Technologies

• Backend: Python (Flask)
• Database: SQLite (schema supports migration to PostgreSQL/MySQL)
• Frontend: HTML, CSS (Bootstrap), JavaScript
• Documentation: UML, DFD, use cases, sequence diagrams

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Getting Started

1. Clone Repository

git clone https://github.com/IgorD-lab/Pharmacy.git
cd Pharmacy

2. Install Dependencies

pip install -r requirements.txt

3. Run Development Server

python app.py

Visit: http://127.0.0.1:5000/

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Screens & Workflow

• Login Page – Secure access for pharmacists
• Dashboard – View pending, approved, and rejected prescriptions
• Processing View – Step-by-step validation results (insurance, doctor, inventory, safety)
• Alert Handling – Clear warnings (yellow = caution, red = critical)
• Decision & Logging – Approve, reject, or override with mandatory comment

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Future Improvements

• UI refinements (simplify prescription processing view)
• Real-time notifications (new prescriptions, failed checks)
• Integration with external medical databases for advanced drug interaction checks
• Detailed audit trail with timestamps for regulatory compliance
• Responsive design for tablets/mobile devices

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Documentation

Full design documentation is included in the repo:

• System Design Document (Apoteka.docx)

This covers DFDs, UML diagrams, database schemas, and detailed process logic.

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Disclaimer

This project is a research prototype and not intended for production medical use. It demonstrates system design, architecture, and proof-of-concept implementation for academic and portfolio purposes.