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.
18 years or older
Inpatient or observation stays within UCLA Health System hospitals
Hemoglobin A1c (A1c) and Thyroid-Stimulating Hormone (TSH) ordered, AND this lab was ordered and resulted within the prior 30 days
Have an A1c or TSH ordered and do not have a result for one of these labs in the prior 30 days
Parallel
OPA
BehavioralThe Our Practice Advisory (OPA) intervention is a behavioral nudge integrated into the electronic health record system. It is designed to prompt providers to reconsider ordering Hemoglobin A1c (A1c) and Thyroid-Stimulating Hormone (TSH) tests if a similar test was performed within the previous 30 days. The OPA aligns with evidence-based guidelines to reduce unnecessary testing, improve resource utilization, and optimize patient care by enhancing clinical decision-making at the point of order entry.
Change in Frequency of Hemoglobin A1c (A1c) and Thyroid-Stimulating Hormone (TSH) Ordered within 30 days of Prior Results
This measure evaluates the impact of a randomized Our Practice Advisory (OPA) intervention on the frequency of Hemoglobin A1c (A1c) and Thyroid-Stimulating Hormone (TSH) tests ordered within 30 days of prior results. Data will be extracted from the UCLA Health Electronic Health Record (EHR) system using a structured query to identify qualifying test orders. Logistic regression will be used to compare the likelihood of A1c or TSH orders within the 30 days between the intervention and control group, adjusting for patient age, sex, and comorbidities. Clustering by providers will be accounted for.
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