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

StatusNot Yet Recruiting
PhaseNot applicable
Started
View on ClinicalTrials.gov ↗

Record History

  1. Study First Submitted
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).
Trial Details
NCT Number NCT07823517
Lead Sponsor Sheba Medical Center
Conditions
(from sponsor)		 High-risk Pregnancy, Hospitalization, Patient Activation, Artificial Intelligence (AI)
Related terms Depression, Postpartum, Patient Participation
Enrollment 200 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov