Trial reportCirculation. Population health and outcomes2026
Effectiveness of Data-Driven Quality Improvement on Hospitalizations and Health Outcomes for People With Coronary Heart Disease in Primary Care (QUEL): A Cluster Randomized Controlled Trial With 24-Month Follow-Up.
Trial report in Circulation. Population health and outcomes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- From Efficacy to Effectiveness: When Proven Therapies Fail.Circulation. Population health and outcomes · 2026Article
Corrections and comments
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Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis trial aimed to test the effectiveness of a data-driven quality improvement program in primary care on cardiovascular hospitalizations, major adverse cardiovascular events (MACE), risk factor profiles, and medication prescriptions at 24 months in people with coronary heart disease (CHD) compared with standard care.
methodsA single-blind, cluster randomized controlled trial recruiting Australian primary care practices (2019-2022) was conducted. Practices using compliant data extraction software and having ≥200 adult patients annually with CHD were the units of randomization, and adults with CHD (who visited their general practitioner in the past 12 months) were the units of analysis. Practices were randomized to intervention (12-month data-driven quality improvement including benchmarking, monthly reporting, and improvement planning) or control (standard care). The primary outcome was the proportion of participants who had unplanned cardiovascular disease hospitalizations at 24 months. Secondary outcomes were MACE, medication prescriptions, risk factor targets, and management planning. Data were extracted from electronic records linked to administrative data.
resultsA total of 51 primary care practices participated, resulting in a patient cohort of 7864. The mean age of the patient cohort was 71.9 (±11.8) years, 68% were men, and 24% had a prior myocardial infarction. At 24 months, there was no significant difference between the groups for unplanned cardiovascular disease hospitalizations (relative risk, 0.91 [95% CI, 0.75-1.10]; MACE, 0.81 [95% CI, 0.61-1.07]; prescription of antiplatelet, 0.94 [95% CI, 0.79-1.13]), statin, 1.03 [95% CI, 0.97-1.09], angiotensin-converting enzyme or angiotensin receptor blocker, 1.00 [95% CI, 0.93-1.07]; risk factor targets for low-density lipoprotein cholesterol, 0.99 [95% CI, 0.86-1.13], systolic blood pressure, 0.97 [95% CI, 0.87-1.09], or smoking, 0.96 [95% CI, 0.57-1.59]; or management planning, 1.02 [95% CI, 0.64-1.63]).
conclusionsA primary care, data-driven quality improvement program did not improve unplanned hospitalizations, MACE, medication prescriptions, achievement of risk factor targets, or management planning for people with CHD. Robust evidence for the use of a data-driven, collaborative approach to improving care for people with CHD in primary care remains elusive. REGISTRATION: URL: https://www.anzctr.org.au; Unique identifier: ACTRN12619001790134.
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