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

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.