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Quality Improvement in Congenital Heart Surgery Requires Data: Is This Asking too Much in Low- and Middle-Income
Debasis Das1, Shubhadeep Das2, Bistra Zheleva3
1Department of Cardiac Surgery, Narayana Hospital(Narayana Health), Howrah, India.
Insights
Low- and middle-income countries (LMICs) face challenges in collecting data for congenital heart surgery quality improvement (QI). Stepwise, local data strategies can drive progress toward safer cardiac care.
Area of Science:
- Cardiology
- Public Health
- Health Informatics
Background:
- Quality improvement (QI) in congenital heart surgery relies on robust data systems.
- Low- and middle-income countries (LMICs) face significant data collection challenges, despite bearing the largest burden of congenital heart disease.
- Mature national registries and benchmarking systems are common in high-income countries but lacking in LMICs.
Purpose of the Study:
- To review the evolving data landscape for congenital heart surgery in LMICs.
- To explore the link between data systems and QI in these regions.
- To identify barriers and propose context-appropriate strategies for sustainable data collection and QI.
Main Methods:
- This narrative review synthesized evidence from published outcome studies, national/regional registry reports, and international databases.
- The review examined the relationship between data systems and QI, barriers to data collection, and strategies for progress.
- Focus was placed on identifying successful models and actionable strategies for LMICs.
Main Results:
- Evidence shows a growing maturation of data systems in LMICs.
- Incremental data collection on key indicators (mortality, morbidity, length of stay) can yield significant QI when combined with local leadership and audit.
- Successful models emphasize collaborative learning networks and simple audit mechanisms.
Conclusions:
- Comprehensive, high-fidelity data collection may be challenging in resource-limited settings.
- Stepwise, local data strategies are a realistic approach to improving congenital cardiac care.
- International collaboration, capacity building, and context-sensitive implementation are crucial for sustainable progress in LMICs.
Abstract:
Quality improvement (QI) in congenital heart surgery depends mainly on the availability of reliable, organized, and usable data. While high-income countries benefit from mature national registries and well-established benchmarking systems, low- and middle-income countries (LMICs), which carry the largest global burden of congenital heart disease, continue to face significant challenges in data collection. This narrative review examines the current evolving data landscape for congenital heart surgery in LMICs, explores the relationship between existence of data systems and QI, identifies persistent barriers to data collection, and proposes context-appropriate strategies for sustainable progress. Evidence from published outcome studies, national and regional registry reports, and some major international databases demonstrates encouraging growth in progressive maturation of data systems across LMICs. Importantly, successful models illustrate that even incremental data collection, when focused on high-impact indicators such as mortality, major morbidity, and hospital length of stay, can generate meaningful improvements when linked with local clinical leadership, simple audit mechanisms, and collaborative learning networks. Although comprehensive, high-fidelity data collection may be unrealistic in many resource-constrained environments, the pursuit of perfection should not impede progress. Stepwise, local data strategies, supported by international collaboration, capacity building, and context-sensitive implementation, offer a realistic and transformative pathway toward safer, more equitable congenital cardiac care in LMICs.
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