Humana. has filed a patent for a method and system to predict commonly billed supplementary medical services based on historical claims data. By analyzing patterns between co-occurring services, the accuracy of predictions is scored using a similarity index. This innovation aims to improve healthcare service planning and delivery. GlobalData’s report on Humana gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Humana, AI for workflow management was a key innovation area identified from patents. Humana's grant share as of January 2024 was 45%. Grant share is based on the ratio of number of grants to total number of patents.

Predicting medical services based on historical claims data

Source: United States Patent and Trademark Office (USPTO). Credit: Humana Inc

A patent application (Publication Number: US20240020766A1) outlines a method for predicting a set or bundle of medical services to be provided to patients. The method involves collecting historical claims data for a group of patients over a specific period, grouping the data into treatment visits, and creating a table with primary and supplementary CPT codes for each visit. By establishing unique combinations and analyzing patterns in billed supplementary codes, the method predicts the most likely set of medical services for each unique combination. The process includes steps such as mapping similar codes, identifying fraudulent billing, and assessing prediction accuracy through testing.

Furthermore, the method includes additional steps like grouping data by service day, removing out-of-network claims, and preparing personalized cost predictions based on demographic data. It also involves identifying potential fraudulent billing by comparing predicted costs with actual billed amounts and using a similarity index to determine prediction accuracy. By applying a Frequent Pattern Growth algorithm and tracking co-occurring codes, the method enhances the accuracy of predicting supplementary CPT codes for specific combinations. Overall, the method aims to streamline the prediction of medical services, improve cost estimation, and detect potential fraudulent billing practices in healthcare settings.

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