Introducing the Large Medical Model: State of the art healthcare cost and risk prediction with transformers trained on patient event sequences

TL;DR

The paper presents the Large Medical Model, a transformer trained on extensive patient data, achieving superior predictions of healthcare costs and risks, thereby advancing healthcare analytics and personalized medicine.

Contribution

Introduction of the Large Medical Model, a transformer-based system trained on 140 million patient records for improved healthcare cost and risk prediction.

Findings

Cost prediction improved by 14.1% over commercial models.

Chronic conditions prediction improved by 1.9% over existing transformers.

Demonstrated ability to identify complex medical patterns and novel patient care relationships.

Abstract

With U.S. healthcare spending approaching $5T (NHE Fact Sheet 2024), and 25% of it estimated to be wasteful (Waste in the US the health care system: estimated costs and potential for savings, n.d.), the need to better predict risk and optimal patient care is evermore important. This paper introduces the Large Medical Model (LMM), a generative pre-trained transformer (GPT) designed to guide and predict the broad facets of patient care and healthcare administration. The model is trained on medical event sequences from over 140M longitudinal patient claims records with a specialized vocabulary built from medical terminology systems and demonstrates a superior capability to forecast healthcare costs and identify potential risk factors. Through experimentation and validation, we showcase the LMM's proficiency in not only in cost and risk predictions, but also in discerning intricate patterns within complex medical conditions and an ability to identify novel relationships in patient care. The LMM is able to improve both cost prediction by 14.1% over the best commercial models and chronic conditions prediction by 1.9% over the best transformer models in research predicting a broad set of conditions. The LMM is a substantial advancement in healthcare analytics, offering the potential to significantly enhance risk assessment, cost management, and personalized medicine.