Comprehension clinical trials at University of California Health
2 in progress, 0 open to eligible people
Patient-centered Precision Medicine Lab Result Communication for Older Adults
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For adults ≥65 years and their providers, the investigators will test the usability and design of a tool to replace standard uniform reporting of lab results to patients and their providers with a new personalized Electronic Health Record (EHR) lab result communication tool that: 1) extracts patient-level data from the EHR; 2) calculates individual risk; and 3) for patients with very low risk, communicates the individualized risk information. The investigators will employ a range of User Experience (UX) research methods to understand how patient and provider users interact with the new lab result communication tool and to assess their comprehension of the lab results. This study will be conducted with both patient and provider participants. The patient participant portion of this study uses a four-arm, design to evaluate three newly designed laboratory result communication template reports compared with the current standard (control) communication. The provider participant portion of this study is non-randomized; all provider participants will review all four template reports. This will include live semi-structured interviews with the participants and review of the template report(s) of the Chronic Kidney Disease (CKD) lab result communication tool. An anonymous in-person template report feedback survey will be provided to the participants to gauge their understanding of the template report(s), clarity of the information presented, and overall satisfaction with the tool. This will be a single-visit interaction with the participant in the UCLA Health geriatric or general medicine patient waiting room.
at UCLA
AI-Driven Consent Simplification Study
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The overarching goal of this pilot is to explore how generative artificial intelligence (genAI) can be used to improve the accessibility and understandability of informed consent materials in clinical research. The study will test the extent to which informed consent text can be improved by large language models (LLM; specifically, ChatGPT and NotebookLM) along with other AI tools (specifically, ElevenLabs) through qualitative and quantitative analyses. Simplifying such forms using genAI may facilitate better comprehension, ensuring truly informed consent. Improving informed consent form (ICF) comprehension can lead to more informed and willing participation in clinical studies. This improved understanding may result in higher enrollment rates, better subject retention, and more accurate data collection as individuals will have a clearer understanding of study procedures and risks.
at UCLA
Our lead scientists for Comprehension research studies include Catherine A Sarkisian, MD, MSHS Arash Naeim, MD, PhD.
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