LLM-Generated Medical Summaries During Hospitalization to Improve Patient Activation in High-Risk Pregnancies

The goal of this clinical trial is to learn if AI-generated medical summaries help hospitalized pregnant participants better understand and actively participate in their own care. The main questions it aims to answer are: Do AI-generated summaries increase participant activation (knowledge, skills, and confidence in managing their health)? How accurate are the AI-generated summaries, as assessed by physicians? Do AI-generated summaries affect depressive symptoms during hospitalization? Researchers will compare participants who receive periodic AI-generated summaries of their medical care with participants who receive standard care to determine whether the summaries improve patient activation during hospitalization. Participants will: Be randomly assigned to receive AI-generated medical summaries or standard care. Complete the Patient Activation Measure (PAM-13) at baseline before the intervention and again after the intervention. Complete the Edinburgh Postnatal Depression Scale (EPDS) at baseline and again after the intervention. Receive up to 3 summaries during their hospitalization (intervention group only).

Inclusion Criteria: * Admitted to the antepartum high-risk department at Sheba Medical Center * Able to provide written informed consent * Able to read and understand Hebrew, English, or Arabic Exclusion Criteria: * Expected hospitalization of less than 3 days