Ahmed Almagazzachi|Ahmed Mustafa|Ashkan Eighaei Sedeh|Alicia González|Anastasiia Polianovskaia|Muhanad Abood|Ameer Abdelrahman|Veronica Muyolema Arce|Talar Acob|Basharat Ali Saleem
Generative Artificial Intelligence in Patient Education: ChatGPT Takes on Hypertension Questions
Capital Health|Capital Health|Capital Health|Capital Health|Capital Health|Capital Health|Capital Health|Capital Health|Capital Health|Regional Medical Center|Capital Health
introduction uncontrolled hypertension significantly contributes development deterioration various medical conditions myocardial infarction chronic kidney disease cerebrovascular events despite common preventable risk factor allcause mortality fraction affected individuals maintain blood pressure desired range recent times growing reliance online platforms medical information providing convenient source information differentiating reliable unreliable information daunting layperson false information potentially hinder timely diagnosis management medical conditions surge accessibility generative artificial intelligence geai technology led increased use obtaining healthrelated information sparked debates among healthcare providers potential misuse misinformation recognizing role geai improving health literacy study aims investigate accuracy aigenerated information specifically related hypertension additionally seeks explore reproducibility information provided geai method nonhumansubject qualitative study devised evaluate accuracy information provided chatgpt regarding hypertension secondary complications frequently asked questions hypertension compiled three study staff internal medicine residents acgmeaccredited program reviewed physician experienced treating hypertension resulting final set 100 questions question posed chatgpt three times study staff majority response assessed recommended guidelines boardcertified internal medicine physician eight years experience reviewed responses categorized two classes based clinical appropriateness appropriate line clinical recommendations inappropriate containing errors descriptive statistical analysis employed assess chatgpt responses accuracy reproducibility result initially pool 130 questions gathered final set 100 questions selected purpose study assessed acceptable standard responses chatgpt responses found appropriate 925 cases inappropriate 75 furthermore chatgpt reproducibility score 93 meaning could consistently reproduce answers conveyed similar meanings across multiple runs conclusion chatgpt showcased commendable accuracy addressing commonly asked questions hypertension results underscore potential geai providing valuable information patients however continued research refinement essential evaluate reliability broader applicability chatgpt within medical field