Data-driven collaborative QUality improvement in Cardiac Rehabilitation (QUICR) to increase program completion: protocol for a cluster randomized controlled trial

Author:

Candelaria DionORCID,Redfern Julie,O’Neil Adrienne,Brieger David,Clark Robyn A,Briffa Tom,Bauman Adrian,Hyun Karice,Cunich Michelle,Figtree Gemma A,Cartledge Susie,Gallagher Robyn

Abstract

Abstract Background Coronary heart disease (CHD) is the leading cause of deaths and disability worldwide. Cardiac rehabilitation (CR) effectively reduces the risk of future cardiac events and is strongly recommended in international clinical guidelines. However, CR program quality is highly variable with divergent data systems, which, when combined, potentially contribute to persistently low completion rates. The QUality Improvement in Cardiac Rehabilitation (QUICR) trial aims to determine whether a data-driven collaborative quality improvement intervention delivered at the program level over 12 months: (1) increases CR program completion in eligible patients with CHD (primary outcome), (2) reduces hospital admissions, emergency department presentations and deaths, and costs, (3) improves the proportion of patients receiving guideline-indicated CR according to national and international benchmarks, and (4) is feasible and sustainable for CR staff to implement routinely. Methods QUICR is a multi-centre, type-2, hybrid effectiveness-implementation cluster-randomized controlled trial (cRCT) with 12-month follow-up. Eligible CR programs (n = 40) and the individual patient data within them (n ~ 2,000) recruited from two Australian states (New South Wales and Victoria) are randomized 1:1 to the intervention (collaborative quality improvement intervention that uses data to identify and manage gaps in care) or control (usual care with data collection only). This sample size is required to achieve 80% power to detect a difference in completion rate of 22%. Outcomes will be assessed using intention-to-treat principles. Mixed-effects linear and logistic regression models accounting for clusters within allocated groupings will be applied to analyse primary and secondary outcomes. Discussion Addressing poor participation in CR by patients with CHD has been a longstanding challenge that needs innovative strategies to change the status-quo. This trial will harness the collaborative power of CR programs working simultaneously on common problem areas and using local data to drive performance. The use of data linkage for collection of outcomes offers an efficient way to evaluate this intervention and support the improvement of health service delivery. Ethics Primary ethical approval was obtained from the Northern Sydney Local Health District Human Research Ethics Committee (2023/ETH01093), along with site-specific governance approvals. Trial registration Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12623001239651 (30/11/2023) (https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=386540&isReview=true).

Funder

National Health and Medical Research Council (NHMRC) Investigator Grant

NHMRC Emerging Career Fellow 2

NHMRC Emerging Leader1 Fellowship

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3