AI Powered Decision Support System for Assisting Medical Staff
- #AI
- #Data science
- #Deep learning
- #Healthcare
- #Machine learning
About the Client
A client is a personalized medicine service provider making cutting-edge science and advanced clinical experience available for medical practitioners.
Business Challenge
Amid the COVID-19 pandemic, the global healthcare system is facing new challenges. A shortage of medical staff and a high workload of hospitals slow down the provision of care to patients, which makes it ineffective in fighting the spread of the virus.
The client wanted to create a decision support system that would help doctors examine patients, record health data into EMR, and get recommendations on treatment for COVID-19 cases.
Solution Overview
We developed the decision support system (DSS) to help the medical staff involved in the fight against COVID-19 prescribe and monitor treatment processes faster and more efficiently regardless of their qualification level. The doctors use DSS to record the medical data of patients with suspected COVID-19. All the information is collected according to the examination protocol. After filling in all the necessary data, the system automatically synchronizes the DSS’s information to the hospital’s medical information system.
Additionally, DSS forces medical staff to follow the protocol, allowing doctors to quickly update treatment and receive recommendations for patients with COVID-19.
Project Description
The DSS allows adding and configuring medical protocols and implements doctor AWP (Any Willing Provider). The protocol consists of rules defined by experts that record the examination results as a patient’s EMR and suggest further steps upon a patient’s treatment history. The first protocol implemented during pilot training was the COVID-19 diagnosis treatment protocol that a doctor must follow during the physical examination.
The DSS system also provides recommendations doctors can apply to treat sick patients. It refers to the protocol, assesses the patient’s status, and gives the doctor recommendations when hospitalization is required or when the patient can continue treatment at home.
For quick access to the AWP, we created a web application that can run from any device connected to the Internet. It synchronizes with the hospital’s MIS via API and allows rapid retrieval of patient data. The doctor AWP UI is generated upon configured rules in the protocol.
After the pilot was integrated and configured, we started rolling out the project to other hospitals per the client’s requirements.
Special attention has been paid to the security subsystem, which allows configuring roles, granularly gives permissions even on a record level, and logs all actions in the system.
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Technological Details
The DSS is implemented on top of a custom rule-based engine, mainly written in Python. PostgreSQL was used as a data storage. For dynamic UI – React.
