Patient record management system for the microsurgery department

About project

The Patient Record Management System operates within the closed network of Kuban State Medical University. It was developed as part of a medical scientific and technological project to collect and analyze data on patients with vertebral defects. The system is utilized in the Microsurgery Department of the State Budgetary Healthcare Institution 'Scientific Research Institute - Regional Clinical Hospital No. 1 named after Professor S. V. Ochapovsky' of the Ministry of Health of the Krasnodar Region.

The system streamlines the collection of analytical and statistical data on patients by providing filtering capabilities in the patient registry and performing automatic calculations based on predefined formulas across various medical indicators.

Facts

Secure and restricted access within the closed university network.
Automates patient data collection and analysis.
Enhances statistical reporting and research capabilities.
Supports real-time data filtering and analytics.
Exportable reports in *.xlsx format.

Customer

Scientific Research Institute - Regional Clinical Hospital No. 1 named after Professor S. V. Ochapovsky, Krasnodar.

Spellsystems Role

SpellSystems was responsible for the full-cycle development and implementation of the Patient Record Management System. The company handled:

  • System architecture and design.
  • Backend and frontend development.
  • Database integration and optimization.
  • Implementation of statistical modules.
  • Deployment and containerization using Docker.
  • Integration with external services (API SMSAero for notifications).

Goal

The goal of the system is to facilitate medical research and patient data management by automating the collection, analysis, and reporting of critical healthcare metrics. This improves patient outcomes and enhances medical research efficiency.

Implementation

The system consists of several key modules:


User Authorization Module

  • Access restricted to authorized users.
  • Doctors must log in with their full name for accountability.
Patient Registry

  • Full patient management capabilities.
  • Adding, modifying, deleting, and archiving records.
  • Advanced filtering options.
  • Export functionality to *.xlsx format.
Patient Card

  • Records patient information including diagnosis, surgery details, health metrics, and follow-up evaluations.
  • Supports multiple clinical scales such as VAS (Visual Analog Scale), ODI (Oswestry Disability Index), and SF-36 Health Survey.
  • Stores CT scans, blood tests, and additional medical indicators.
Statistics Module

  • Automates metric calculations based on selected filters.
  • Computes mean, median, confidence intervals, and standard deviations.
  • Analyzes trends such as BMI distribution and surgery intervals.
  • Exportable results for further research and analysis.

Technologies

Basic technologies
1
  • Python
Storing and working with data
2
  • PostgreSQL
Web Interface
3
  • React.js
Infrastructure
4
  • Docker