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Best Definitions of Multimorbidity to Identify Patients With High Health Care Resource Utilization

Carole E. Aubert, Jeffrey L. Schnipper, Marie Roumet, Pedro Marques‐Vidal, Jérôme Stirnemann, Andrew D. Auerbach, Eyal Zimlichman, Sunil Kripalani, Eduard E. Vasilevskis, Edmondo Robinson, Grant Fletcher, Drahomir Aujesky, Andreas Limacher, Jacques Donzé

2020Mayo Clinic Proceedings Innovations Quality & Outcomes38 citationsDOIOpen Access PDF

Abstract

ObjectiveTo compare different definitions of multimorbidity to identify patients with higher health care resource utilization.Patients and MethodsWe used a multinational retrospective cohort including 147,806 medical inpatients discharged from 11 hospitals in 3 countries (United States, Switzerland, and Israel) between January 1, 2010, and December 31, 2011. We compared the area under the receiver operating characteristic curve (AUC) of 8 definitions of multimorbidity, based on International Classification of Diseases codes defining health conditions, the Deyo-Charlson Comorbidity Index, the Elixhauser-van Walraven Comorbidity Index, body systems, or Clinical Classification Software categories to predict 30-day hospital readmission and/or prolonged length of stay (longer than or equal to the country-specific upper quartile). We used a lower (yielding sensitivity ≥90%) and an upper (yielding specificity ≥60%) cutoff to create risk categories.ResultsDefinitions had poor to fair discriminatory power in the derivation (AUC, 0.61-0.65) and validation cohorts (AUC, 0.64-0.71). The definitions with the highest AUC were number of (1) health conditions with involvement of 2 or more body systems, (2) body systems, (3) Clinical Classification Software categories, and (4) health conditions. At the upper cutoff, sensitivity and specificity were 65% to 79% and 50% to 53%, respectively, in the validation cohort; of the 147,806 patients, 5% to 12% (7474 to 18,008) were classified at low risk, 38% to 55% (54,484 to 81,540) at intermediate risk, and 32% to 50% (47,331 to 72,435) at high risk.ConclusionOf the 8 definitions of multimorbidity, 4 had comparable discriminatory power to identify patients with higher health care resource utilization. Of these 4, the number of health conditions may represent the easiest definition to apply in clinical routine. The cutoff chosen, favoring sensitivity or specificity, should be determined depending on the aim of the definition.

Topics & Concepts

MedicineQuartileComorbidityReceiver operating characteristicCutoffCohortRetrospective cohort studyHealth careMultimorbidityCohort studyEmergency medicineInternal medicineConfidence intervalQuantum mechanicsEconomicsPhysicsEconomic growthChronic Disease Management StrategiesHeart Failure Treatment and ManagementPrimary Care and Health Outcomes