Evaluating the Quality of Postpartum Hemorrhage Nursing Care Plans Generated by Artificial Intelligence Models

Abstract

Background:With the rapidly advancing technological landscape of health care, evaluating the potential use of artificial intelligence (AI) models to prepare nursing care plans is of great importance.Purpose:The purpose of this study was to evaluate the quality of nursing care plans created by AI for the management of postpartum hemorrhage (PPH).Methods:This cross-sectional exploratory study involved creating a scenario for an imaginary patient with PPH. Information was put into 3 AI platforms (GPT-4, LaMDA, Med-PaLM) on consecutive days without prior conversation. Care plans were evaluated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) scale.Results:Med-PaLM exhibited superior quality in developing the care plan compared with LaMDA (Z = 4.354; P = .000) and GPT-4 (Z = 3.126; P = .029).Conclusions:Our findings suggest that despite the strong performance of Med-PaLM, AI, in its current state, is unsuitable for use with real patients.