Cross-linking clinical practice guidelines for multimorbidity

Abstract

Clinical practice guidelines (CPGs) play a pivotal role in elevating healthcare quality. However, their traditional single-disease focus falls short in addressing the complexities of multimorbidity, a condition increasingly prevalent in an aging population. This discrepancy necessitates that healthcare providers juggle multiple guidelines to formulate comprehensive care plans for such patients. Our paper introduces an innovative methodology designed to streamline this process by cross-linking different CPGs, thereby facilitating more efficient navigation across various guidelines. This approach is grounded in language-agnostic principles and leverages Semantic Web technologies to connect guideline terms to biomedical knowledge sources like SNOMED. Our methodology has undergone validation by medical practitioners and guideline developers, particularly within the context of Dutch CPGs. The results of these experiments underscore the effectiveness of our approach, demonstrating its potential to contribute to key issues associated with CPGs in multimorbidity scenarios, such as computer-interpretable clinical guidelines and the interaction of multiple CPGs. Furthermore, the outcomes of this method extend beyond immediate practical applications, offering valuable insights for the enhancement of guideline databases and medical knowledge bases like SNOMED. By bridging gaps between separate guidelines, our method represents a step forward in the integrated management of multimorbidity in CPGs.