PT  - JOURNAL ARTICLE
AU  - Clough, Reece Alexander James
AU  - Sparkes, William Anthony
AU  - Clough, Oliver Thomas
AU  - Sykes, Joshua Thomas
AU  - Steventon, Alexander Thomas
AU  - King, Kate
TI  - Transforming healthcare documentation: harnessing the potential of AI to generate discharge summaries
AID  - 10.3399/BJGPO.2023.0116
DP  - 2024 Apr 01
TA  - BJGP Open
PG  - BJGPO.2023.0116
VI  - 8
IP  - 1
4099  - http://bjgpopen.org/content/8/1/BJGPO.2023.0116.short
4100  - http://bjgpopen.org/content/8/1/BJGPO.2023.0116.full
SO  - BJGP Open2024 Apr 01; 8
AB  - Background Hospital discharge summaries play an essential role in informing GPs of recent admissions to ensure excellent continuity of care and prevent adverse events; however, they are notoriously poorly written, time-consuming, and can result in delayed discharge.Aim To evaluate the potential of artificial intelligence (AI) to produce high-quality discharge summaries equivalent to the level of a doctor who has completed the UK Foundation Programme.Design & setting Feasibility study using 25 mock patient vignettes.Method Twenty-five mock patient vignettes were written by the authors. Five junior doctors wrote discharge summaries from the case vignettes (five each). The same case vignettes were input into ChatGPT. In total, 50 discharge summaries were generated; 25 by Al and 25 by junior doctors. Quality and suitability were determined through both independent GP evaluators and adherence to a minimum dataset.Results Of the 25 AI-written discharge summaries 100% were deemed by GPs to be of an acceptable quality compared with 92% of the junior doctor summaries. They both showed a mean compliance of 97% with the minimum dataset. In addition, the ability of GPs to determine if the summary was written by ChatGPT was poor, with only a 60% accuracy of detection. Similarly, when run through an AI-detection tool all were recognised as being very unlikely to be written by AI.Conclusion AI has proven to produce discharge summaries of equivalent quality to a junior doctor who has completed the UK Foundation Programme; however, larger studies with real-world patient data with NHS-approved AI tools will need to be conducted.