Key result
This paper outlines the protocol for a mixed-methods process evaluation of a data-driven quality improvement program in primary care to improve secondary prevention of cardiovascular disease; no results are reported.
Why the study?
Practice-level quality improvement initiatives using rapidly advancing technology offer a multidimensional approach to reduce cardiovascular disease burden, prompting a protocol to systematically evaluate a data-driven intervention within the QUEL trial.
Does a data-driven quality improvement program reduce CVD hospitalisations in patients with coronary heart disease in primary care?
Does a data-driven quality improvement program reduce CVD hospitalisations in patients with coronary heart disease in primary care?
This protocol outlines the process evaluation of a data-driven quality improvement intervention in primary care aimed at enhancing secondary prevention of cardiovascular disease.
Protocol for process evaluation of data-driven QI program; leaves open whether intervention reduces CVD hospitalizations in primary care CHD patients.
BACKGROUND: Practice-level quality improvement initiatives using rapidly advancing technology offers a multidimensional approach to reduce cardiovascular disease burden. For the "QUality improvement in primary care to prevent hospitalisations and improve Effectiveness and efficiency of care for people Living with heart disease" (QUEL) cluster randomised controlled trial, a 12-month quality improvement intervention was designed for primary care practices to use data and implement progressive changes using "Plan, Do, Study, Act" cycles within their practices with training in a series of interactive workshops. This protocol aims to describe the systematic methods to conduct a process evaluation of the data-driven intervention within the QUEL study. METHODS: A mixed-method approach will be used to conduct the evaluation. Quantitative data collected throughout the intervention period, via surveys and intervention materials, will be used to (1) identify the key elements of the intervention and how, for whom and in what context it was effective; (2) determine if the intervention is delivered as intended; and (3) describe practice engagement, commitment and capacity associated with various intervention components. Qualitative data, collected via semi-structured interviews and open-ended questions, will be used to gather in-depth understanding of the (1) satisfaction, utility, barriers and enablers; (2) acceptability, uptake and feasibility, and (3) effect of the COVID-19 pandemic on the implementation of the intervention. CONCLUSION: Findings from the evaluation will provide new knowledge on the implementation of a complex, multi-component intervention at practice-level using their own electronic patient data to enhance secondary prevention of cardiovascular disease. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) number ACTRN12619001790134.
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Hafiz et al. (2022) studied Coronary Heart Disease (n=15,000). Data-driven quality improvement program (QUEL) vs. Usual care was evaluated on CVD hospitalisations (main trial) / Process evaluation metrics. This paper outlines the protocol for a mixed-methods process evaluation of a data-driven quality improvement program in primary care to improve secondary prevention of cardiovascular disease; no results are reported.
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