Enhancing Clinical Data Quality to Improve Patient Care in Rural Health Facilities

Abstract

WHO recognizes that high-quality research is not just a scientific pursuit but a crucial factor in achieving global health, health equity, and economic development. It is not just about the numbers but about the lives we can save and improve. In this context, four research priority areas have been identified: prioritizing health needs, building research capacity, ensuring good research practice, and ensuring good evidence is translated into practice. Local health research tailored to local needs remains an important global health goal, with the potential to revolutionize patient care in rural health facilities. Researchers and policymakers in low- and middle-income countries have expressed serious concerns about the limited access to high-quality data, a fundamental requirement for reliable and valid research. The assessment of data quality is typically categorized into five key areas: availability, usability, dependability, relevance, and presentation quality. This concept is further clarified by demonstrating how a robust healthcare data environment can enhance patient management through research efforts. The term ‘health data environment' encompasses the entire process of gathering, storing, managing, analysing, and utilizing health-related data to improve patient care and healthcare policies through informed decision-making. In this context, we present the challenges that undermine the quality of research data and propose solutions. Specifically, we identify the lack of adequate human resources, reliance on paper-based records systems, and the high costs of internet connectivity as the primary barriers to collecting and sharing high-quality data for research in low-resource settings. To tackle these challenges, we advocate for governments and funding institutions to invest in data management and communication systems, recruit and train data management staff to support clinicians, and reduce connectivity costs. Furthermore, we propose the deployment of a decentralized system as a cost-effective and less labor-intensive solution that only requires data entry staff at health facilities in resource-limited settings. This article explores current data collection, storage, and interpretation challenges and proposes innovative improvement solutions. It emphasizes the transformative potential of digitization, standardization, and staff training to enhance data quality. It further addresses the impact of quality data on evidence-based practice, ultimately leading to improved health outcomes. Focusing on rural healthcare facilities sheds light on the unique barriers these settings face, proposing tailored strategies that can bridge the gap between urban and rural health service delivery. These insights offer valuable guidance for policymakers, healthcare administrators, and practitioners striving to improve patient care in rural areas through data-driven strategies.