Data-driven collaborative QUality improvement in Cardiac Rehabilitation (QUICR) to increase program completion:...

Area of Science:

• Cardiology
• Public Health
• Health Services Research

Background:

• Coronary heart disease (CHD) is a leading global cause of mortality and morbidity.
• Cardiac rehabilitation (CR) is crucial for secondary prevention in CHD patients but suffers from low completion rates.
• Variable CR program quality and data systems hinder effective patient care and outcomes.

Purpose of the Study:

• To evaluate a data-driven collaborative quality improvement intervention for CR programs.
• To determine if the intervention increases CR program completion rates in CHD patients.
• To assess the intervention's impact on hospital admissions, emergency visits, mortality, costs, and adherence to CR guidelines.

Main Methods:

• A multi-centre, type-2, hybrid effectiveness-implementation cluster-randomized controlled trial (cRCT).
• 40 CR programs and approximately 2,000 patients randomized to intervention (data-driven quality improvement) or control (usual care).
• 12-month follow-up with intention-to-treat analysis using mixed-effects models.

Main Results:

• The study aims to detect a 22% difference in CR completion rates.
• Secondary outcomes include reductions in hospital admissions, emergency department presentations, deaths, and costs.
• The intervention's feasibility, sustainability, and impact on guideline adherence will be assessed.

Conclusions:

• Innovative strategies are needed to address low CR participation in CHD patients.
• This trial will leverage collaborative efforts and local data to enhance CR program performance.
• Data linkage will efficiently evaluate the intervention and improve health service delivery.