Predicting hospice eligibility among dementia patients using language models.

ABSTRACT:

Introduction

Alzheimer's disease and related dementias (ADRD) are increasing in prevalence, and access to potential benefits of hospice care remains challenging. Large language models (LLMs), like GPT-4o, applied to electronic health records (EHRs) could support decisions by estimating mortality risk.

Methods

We analyzed patients with ADRD diagnosis from two academic medical centers. GPT-4o was used to estimate 6-month mortality risk from discharge summaries without any retraining or preprocessing. We used Cox regression to assess associations between predictions and time to death.

Results

Of 9872 individuals, 3563 (36%) died within 6 months. GPT-4o predictions stratified risk of death within 6 months (log-rank p < 0.001, area under the curve [AUC] = 0.79); prediction

SUBMITTER: McCoy TH 

PROVIDER: S-EPMC12603788 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature