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BMJ Publishing Group, BMJ Medicine, 1(1), p. e000247, 2022

DOI: 10.1136/bmjmed-2022-000247

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Measuring multimorbidity in research: Delphi consensus study

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

ObjectiveTo develop international consensus on the definition and measurement of multimorbidity in research.DesignDelphi consensus study.SettingInternational consensus; data collected in three online rounds from participants between 30 November 2020 and 18 May 2021.ParticipantsProfessionals interested in multimorbidity and people with long term conditions were recruited to professional and public panels.Results150 professional and 25 public participants completed the first survey round. Response rates for rounds 2/3 were 83%/92% for professionals and 88%/93% in the public panel, respectively. Across both panels, the consensus was that multimorbidity should be defined as two or more long term conditions. Complex multimorbidity was perceived to be a useful concept, but the panels were unable to agree on how to define it. Both panels agreed that conditions should be included in a multimorbidity measure if they were one or more of the following: currently active; permanent in their effects; requiring current treatment, care, or therapy; requiring surveillance; or relapsing-remitting conditions requiring ongoing care. Consensus was reached for 24 conditions to always include in multimorbidity measures, and 35 conditions to usually include unless a good reason not to existed. Simple counts were preferred for estimating prevalence and examining clustering or trajectories, and weighted measures were preferred for risk adjustment and outcome prediction.ConclusionsPrevious multimorbidity research is limited by inconsistent definitions and approaches to measuring multimorbidity. This Delphi study identifies professional and public panel consensus guidance to facilitate consistency of definition and measurement, and to improve study comparability and reproducibility.