3 Clinical Trials for Various Conditions
Our Practice Advisory (OPA) are essential tools in clinical decision-making. The alerts are designed to guide providers towards evidence-based practices and improve patient outcomes. The focus of this initiative is on Hemoglobin A1c (A1c) and Thyroid-Stimulating Hormone (TSH) testing, with the goal of addressing unnecessary repeat testing within a 30-day timeframe, which rarely yields significant new insights. Although randomization occurs at the patient level, the primary outcome of this study focuses on provider behavior and decision-making. By focusing on this specific intervention, the study aims to optimize resource use, align test ordering with evidence-based guidelines, and support improved patient outcomes. The results of this evaluation will help refine OPAs and guide broader strategies for implementing clinical decision support tools across healthcare systems.
This is a three-arm pragmatic RCT of 238 outpatient physicians at a large academic health system, randomized 1:1:1 to one of two AI scribe tools or a usual-care control group. The two-month study will observe and compare the effects of each tool prior to system-wide roll out of selected tool (anticipated Spring 2025). We will use covariate-constrained randomization to balance the arms in terms of physician baseline time in notes, survey-measured level of burnout, and clinic days per week. The primary purpose of the initiative is to improve quality, efficiency, and business operations at University of California, Los Angeles (UCLA) Health, and this initiative is not being done for research purposes. The results of this operational initiative will inform the widespread roll out of AI scribe tools across all providers within the UCLA Health System. Nevertheless, the UCLA study team plans to rigorously examine and publish the impact of this intervention across the health system, which is why the study team pre-registered the initiative.
The purpose of this study is to determine if a simple 'pick-list' menu applied to a handheld computer's time-motion program can be used to record reliably what a hospital-based doctor does while working a shift in the hospital. In this study reliability will be measured by comparing the data collected by at least two different observers recording data from the same hospitalist during the same period of time.