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Generative artificial intelligence writing open notes: A mixed methods assessment of the functionality of GPT 3.5 and GPT 4.0

Authors :
Anna Kharko
Brian McMillan
Josefin Hagström
Irene Muli
Gail Davidge
Maria Hägglund
Charlotte Blease
Source :
Digital Health, Vol 10 (2024)
Publication Year :
2024
Publisher :
SAGE Publishing, 2024.

Abstract

Background Worldwide, patients are increasingly being offered access to their full online clinical records including the narrative reports written by clinicians (so-called “open notes”). Against these developments, there is growing interest in the use of generative artificial intelligence (AI) such as OpenAI's ChatGPT to co-assist clinicians with patient-facing documentation. Objective This study aimed to explore the effectiveness of OpenAI's ChatGPT 3.5 and GPT 4.0 in generating three patient-facing clinical notes from fictional general practice narrative reports. Methods On 1 October 2023 and 1 November 2023, we used ChatGPT 3.5 and 4.0 to generate notes for three validated fictional general practice notes, using a prompt in the style of a British primary care note for three commonly presented conditions: (1) type 2 diabetes, (2) major depressive disorder, and (3) a differential diagnosis for suspected bowel cancer. Outputs were analyzed for reading ease, sentiment analysis, empathy, and medical fidelity. Results ChatGPT 3.5 and 4.0 wrote longer notes than the original, and embedded more second person pronouns, with ChatGPT 3.5 scoring higher on both. ChatGPT expanded abbreviations, but readability metrics showed that the notes required a higher reading proficiency, with ChatGPT 3.5 demanding the most advanced level. Across all notes, ChatGPT offered higher signatures of empathy across cognitive, compassion/sympathy, and prosocial cues. Medical fidelity ratings varied across all three cases with ChatGPT 4.0 rated superior. Conclusions While ChatGPT improved sentiment and empathy metrics in the transformed notes, compared to the original they also required higher reading proficiency and omitted details impacting medical fidelity.

Details

Language :
English
ISSN :
20552076
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Digital Health
Publication Type :
Academic Journal
Accession number :
edsdoj.8d6e02cbf3044249b01a2b062059efd7
Document Type :
article
Full Text :
https://doi.org/10.1177/20552076241291384