MUMBAI, India, Oct. 12 -- Intellectual Property India has published a patent application (202641118908 A) filed by Mlr Institute Of Technology; and Marri Laxman Reddy Institute Of Technology And Management on October 05, 2026, for Artificial Intelligence-Based System And Method For Real-Time Prediction And Management Of Healthcare Costs.
Inventors include Dr. P. Subhashini; Ms. M. Leshwitha; Mr. E. Shivanath; Mr. K. Shivaji; and Ms. S. Hasini.
The application for the patent was published on October 09, 2026, under issue no. 41/2026.
Abstract: The present invention relates to an artificial intelligence-based system and method for real-time prediction and management of healthcare costs. The system is configured to receive and process healthcare-related data comprising patient clinical records, diagnostic reports, treatment plans, medication information, hospital billing data, insurance policy information, historical expenditure data, and other cost-related parameters. A prediction engine processes the received data using one or more machine learning models to generate a dynamic estimate of healthcare expenditure associated with a patient, treatment, procedure, or episode of care. The system continuously updates the predicted expenditure based on changes in diagnosis, treatment, medication, procedures, insurance coverage, and billing information. An anomaly detection module is configured to identify potential duplicate billing entries, abnormal charges, pricing deviations, and other inconsistencies in healthcare expenditure data. An optimization module further determines one or more cost-related alternatives based on applicable insurance coverage, healthcare provider network information, medication costs, procedure costs, and other predefined parameters. The system generates real-time alerts when a predicted expenditure exceeds a predefined threshold, an insurance coverage limit, or another configured financial parameter. The system thereby facilitates prospective estimation, monitoring, and management of healthcare expenditure during a patient care episode.
Disclaimer: Curated by HT Syndication.
