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Conference Paper


Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence


Computer Sciences


Multimorbidity, the coexistence of two or more health conditions, has become more prevalent as mortality rates in many countries have declined and their populations have aged. Multimorbidity presents significant difficulties for Clinical Decision Support Systems (CDSS), particularly in cases where recommendations from relevant clinical guidelines offer conflicting advice. A number of research groups are developing computer-interpretable guideline (CIG) modeling formalisms that integrate recommendations from multiple Clinical Practice Guidelines (CPGs) for knowledge-based multimorbidity decision support. In this paper we describe work towards the development of a framework for comparing the different approaches to multimorbidity CIG-based clinical decision support (MGCDS). We present (1) a set of features for MGCDS, which were derived using a literature review and evaluated by physicians using a survey, and (2) a set of benchmarking case studies, which illustrate the clinical application of these features. This work represents the first necessary step in a broader research program aimed at the development of a benchmark framework that allows for standardized and comparable MGCDS evaluations, which will facilitate the assessment of functionalities of MGCDS, as well as highlight important gaps in the state-of-the-art. We also outline our future work on developing the framework, specifically, (3) a standard for reporting MGCDS solutions for the benchmark case studies, and (4) criteria for evaluating these MGCDS solutions. We plan to conduct a large-scale comparison study of existing MGCDS based on the comparative framework.