Assessing Knowledge Risk Management in Healthcare: A Case Study at a Medical Sciences University

Abstract

Research on knowledge risks and their management within organizations remains limited, particularly in empirical contexts. Replication studies are essential to validate findings and advance scientific understanding. Knowledge Risk Management (KRM) is especially critical in healthcare organizations, where effectively managing knowledge-related risks can profoundly influence patient safety and service quality. This study develops a comprehensive KRM framework tailored to a Medical Sciences University healthcare setting. Utilizing a mixed-methods approach—including interviews, literature review, and the Delphi technique—47 knowledge risks were identified and classified across key healthcare process phases. To account for the inherent subjectivity in expert judgments, risk probabilities were quantified using triangular fuzzy numbers. Results indicate significant gaps in knowledge and information flow, leading to inflated risk perceptions and insufficient data on risk factors. The findings underscore the urgent need to integrate advanced KRM tools and risk network models to improve decision-making and risk mitigation in healthcare environments. This research advances both theoretical and practical insights into KRM, highlighting its pivotal role in enhancing healthcare risk assessment and management. Moreover, it emphasizes the value of replication studies for fostering knowledge accumulation and theory development in management science.