Ellershaw, Simon;
Tomlinson, Christopher;
Burton, Oliver E;
Frost, Thomas;
Hanrahan, John Gerrard;
Khan, Danyal Zaman;
Horsfall, Hugo Layard;
... Dobson, Richard; + view all
(2024)
Automated Generation of Hospital Discharge Summaries Using Clinical Guidelines and Large Language Models.
In:
AAAI 2024 SSS on Clinical FMs.
(pp. pp. 1-8).
Stanford University: Stanford, California, USA.
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Abstract
Discharge summaries are essential yet time-consuming documents doctors write at the end of a patient's hospital stay. They are the primary form of communication between hospital and community care teams. The automatic generation of summaries could reduce the administrative burden on doctors. We propose to use large language models, few-shot prompted by clinical guidance, to perform this task. Unlike previous supervised approaches, our method does not require a large training dataset, can accept full-length physician notes as inputs and is explicitly guided by clinical best practice. We implemented such a system using Royal College of Physicians London guidelines, GPT-4-turbo and MIMIC-III physician notes. 53 summaries were evaluated by 10 clinicians and found to have a micro accuracy of 0.81. Finally, we discuss methodical limitations and the required future improvements to the evaluation framework.
| Type: | Proceedings paper |
|---|---|
| Title: | Automated Generation of Hospital Discharge Summaries Using Clinical Guidelines and Large Language Models |
| Event: | AAAI 2024 Spring Symposium on Clinical Foundation Models |
| Location: | Stanford University, Stanford, California |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://openreview.net/forum?id=1kDJJPppRG |
| Language: | English |
| Additional information: | This is an Open Access article published under a Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Large Language Models, Discharge Summaries, Clinical Guidelines, Automation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10191468 |
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