A large portion of the premium that Health plans earn seems to be spent on processing health claims by means of making payments and extra fees. By automating the claims adjudication process, Health plans could minimise their costs and price their services more competitively. Competitive premium pricing and a streamlined claims process both lead to better experience and engagement.

Given below is the approach that CitiusTech follows to automate claims adjudication:

• End to End AI-ML solution that easily integrates into existing workflow

• Python based data layer for storage of daily extracts

• Automated workflows for model development, monitoring and deployment cycles.

• Scalable ML Production server and MySQL database that houses Prediction, Evaluation, Retraining and Drift APIs which run automatically as per the pre-determined schedule

• Scientific and customized Composite Drift score for easy and regular detection of drift in data

• State of the art Model Performance dashboard that aids business user in adoption to AI-ML results and also provides business user control

Case Study: A leading Managed care Organization had 800,000 subscribers and handle 150,000 to 200,000 suspended claims monthly. They were keen to reduce costs by decreasing manual adjudication on suspended claims.​ By automating the adjudication process the client achieved a saving of ~USD 2M annually.

CitiusTech's Payer vertical is focussed on delivering specialized solutions and services across the healthcare digital value chain - spanning interoperability, data & analytics, digital engineering, provider performance management and member experience management.