Phase 1 Implementation of LLM-generated Discharge Summaries showing high Adoption in a Dutch Academic Hospital

arXiv cs.CL Papers
llm healthcare discharge-summaries ehr clinical-pilot

Summary

A 9-week pilot at a Dutch academic hospital shows 58% of admissions used LLM-generated discharge drafts, with 87% of clinicians reporting reduced documentation time and 91% intending continued use.

arXiv:2604.19774v1 Announce Type: new Abstract: Writing discharge summaries to transfer medical information is an important but time-consuming process that can be assisted by Large Language Models (LLMs). This prospective mixed methods pilot study evaluated an Electronic Health Record (EHR)-integrated LLM to generate discharge summaries drafts. In total, 379 discharge summaries were generated in clinical practice by 21 residents and 4 physician assistants during 9 weeks in our academic hospital. LLM-generated text was copied in 58.5% of admissions, and identifiable LLM content could be traced to 29.1% of final discharge letters. Notably, 86.9% of users self-reported a reduction in documentation time, and 60.9% a reduction in administrative workload. Intent to use after the pilot phase was high (91.3%), supporting further implementation of this use-case. Accurately measuring the documentation time of users on discharge summaries remains challenging, but will be necessary for future extrinsic evaluation of LLM-assisted documentation.
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# Phase 1 Implementation of LLM-generated Discharge Summaries showing high Adoption in a Dutch Academic Hospital
Source: [https://arxiv.org/abs/2604.19774](https://arxiv.org/abs/2604.19774)
[View PDF](https://arxiv.org/pdf/2604.19774)

> Abstract:Writing discharge summaries to transfer medical information is an important but time\-consuming process that can be assisted by Large Language Models \(LLMs\)\. This prospective mixed methods pilot study evaluated an Electronic Health Record \(EHR\)\-integrated LLM to generate discharge summaries drafts\. In total, 379 discharge summaries were generated in clinical practice by 21 residents and 4 physician assistants during 9 weeks in our academic hospital\. LLM\-generated text was copied in 58\.5% of admissions, and identifiable LLM content could be traced to 29\.1% of final discharge letters\. Notably, 86\.9% of users self\-reported a reduction in documentation time, and 60\.9% a reduction in administrative workload\. Intent to use after the pilot phase was high \(91\.3%\), supporting further implementation of this use\-case\. Accurately measuring the documentation time of users on discharge summaries remains challenging, but will be necessary for future extrinsic evaluation of LLM\-assisted documentation\.

## Submission history

From: Nettuno Nadalini \[[view email](https://arxiv.org/show-email/3099e276/2604.19774)\] **\[v1\]**Fri, 27 Mar 2026 16:21:33 UTC \(448 KB\)

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