Designing a Data-Driven Clinical Audit Model for Quality Improvement in Healthcare Service Delivery - Damilola Oluyemi Merotiwon; Opeyemi Olamide Akintimehin; Opeoluwa Oluwanifemi Akomolafe (International Journal of Scientific Research in Science and Technology, 2024)
Clinical audits are essential mechanisms for evaluating and enhancing the quality of healthcare service delivery. However, traditional audit processes often suffer from inefficiencies due to fragmented data sources, manual evaluations, and lack of real-time feedback mechanisms. With the increasing availability of electronic health data and analytics tools, there is an urgent need for a model that integrates these assets into a coherent, data-driven clinical audit framework. This paper proposes a comprehensive model that utilizes structured health data, predictive analytics, and feedback loops to enhance clinical audit efficacy across diverse healthcare settings. The model was developed using a design science approach and evaluated through pilot implementations in three tertiary hospitals. Results show measurable improvements in care delivery, compliance with clinical guidelines, and patient outcomes. The study underscores the transformative potential of data-driven audits in advancing evidence-based quality improvement practices and provides a replicable framework for healthcare institutions aiming to institutionalize continuous performance monitoring.
Keywords: Clinical audits; data-driven models; healthcare quality; electronic health records; predictive analytics; performance improvement