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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

  • Julie Redfern*
  • , Nashid Hafiz
  • , Qiang Tu
  • , Andrew Knight
  • , Charlotte Hespe
  • , Clara K Chow
  • , Tom Briffa
  • , Robyn Gallagher
  • , Christopher M Reid
  • , David Hare
  • , Deborah Manandi
  • , Nicholas Zwar
  • , Mark Woodward
  • , Stephen Jan
  • , Emily R Atkins
  • , Tracey-Lea Laba
  • , Elizabeth Halcomb
  • , Laurent Billot
  • , Tim Usherwood
  • , Karice Hyun
  • *Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Background: 

This 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.

Methods: 

A 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.

Results: 

A 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]).

Conclusions: 

A 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/Trial/Registration/TrialReview.aspx?ACTRN=12619001790134; Unique identifier: ACTRN12619001790134.

Original languageEnglish
Article numbere012904
JournalCirculation. Population health and outcomes
DOIs
Publication statusE-pub ahead of print - 15 Apr 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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