F. C. Dos Santos, Lisa G Johnson, Olatunde O. Madandola, Karen J B Priola, Yingwei Yao, Tamara G. R. Macieira, Gail M. Keenan
{"title":"An example of leveraging AI for documentation: ChatGPT-generated nursing care plan for an older adult with lung cancer.","authors":"F. C. Dos Santos, Lisa G Johnson, Olatunde O. Madandola, Karen J B Priola, Yingwei Yao, Tamara G. R. Macieira, Gail M. Keenan","doi":"10.1093/jamia/ocae116","DOIUrl":null,"url":null,"abstract":"OBJECTIVE\nOur article demonstrates the effectiveness of using a validated framework to create a ChatGPT prompt that generates valid nursing care plan suggestions for one hypothetical older patient with lung cancer.\n\n\nMETHOD\nThis study describes the methodology for creating ChatGPT prompts that generate consistent care plan suggestions and its application for a lung cancer case scenario. After entering a nursing assessment of the patient's condition into ChatGPT, we asked it to generate care plan suggestions. Subsequently, we assessed the quality of the care plans produced by ChatGPT.\n\n\nRESULTS\nWhile not all the suggested care plan terms (11 out of 16) utilized standardized nursing terminology, the ChatGPT-generated care plan closely matched the gold standard in scope and nature, correctly prioritizing oxygenation and ventilation needs.\n\n\nCONCLUSION\nUsing a validated framework prompt to generate nursing care plan suggestions with ChatGPT demonstrates its potential value as a decision support tool for optimizing cancer care documentation.","PeriodicalId":236137,"journal":{"name":"Journal of the American Medical Informatics Association : JAMIA","volume":"36 29","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Medical Informatics Association : JAMIA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/jamia/ocae116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
OBJECTIVE
Our article demonstrates the effectiveness of using a validated framework to create a ChatGPT prompt that generates valid nursing care plan suggestions for one hypothetical older patient with lung cancer.
METHOD
This study describes the methodology for creating ChatGPT prompts that generate consistent care plan suggestions and its application for a lung cancer case scenario. After entering a nursing assessment of the patient's condition into ChatGPT, we asked it to generate care plan suggestions. Subsequently, we assessed the quality of the care plans produced by ChatGPT.
RESULTS
While not all the suggested care plan terms (11 out of 16) utilized standardized nursing terminology, the ChatGPT-generated care plan closely matched the gold standard in scope and nature, correctly prioritizing oxygenation and ventilation needs.
CONCLUSION
Using a validated framework prompt to generate nursing care plan suggestions with ChatGPT demonstrates its potential value as a decision support tool for optimizing cancer care documentation.