• Christiane Muth, Hanna Kirchner, Marjan van den Akker, Martin Scherer, and Paul P Glasziou.
• Institute of General Practice, Johann Wolfgang Goethe University, Theodor-Stern-Kai 7, D-60590 Frankfurt, Germany. Electronic address: muth@allgemeinmedizin.uni-frankfurt.de.
• J Clin Epidemiol. 2014 Nov 1;67(11):1242-50.

ObjectivesTo develop a framework to identify and classify interactions within and among treatments and conditions and to test this framework with guidelines on chronic heart failure (CHF) and its frequent comorbidity.Study Design And SettingText analysis of evidence-based clinical practice guidelines on CHF and 18 conditions co-occurring in ≥5% of CHF patients (2-4 guidelines per disease). We extracted data on interactions between CHF and comorbidity and key recommendations on diagnostic and therapeutic management. From a subset of data, we derived 13 subcategories within disease-disease (Di-Di-I), disease-drug (Di-D-I), drug-drug interactions (DDI) and synergistic treatments. We classified the interactions and tested the interrater reliability, refined the framework, and agreed on the matrix of interactions.ResultsWe included 48 guidelines; two-thirds provided information about comorbidity. In total, we identified N = 247 interactions (on average, 14 per comorbidity): 68 were Di-Di-I, 115 were Di-D-I, 12 were DDI, and 52 were synergisms. All 18 comorbidities contributed at least one interaction.ConclusionThe interaction matrix provides a structure to present different types of interactions between an index disease and comorbidity. Guideline developers may consider the matrix to support clinical decision making in multimorbidity. Further research is needed to show its relevance to improve guidelines and health outcomes.Copyright © 2014 Elsevier Inc. All rights reserved.

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