{"doi":"10.3399/bjgp19x704657","title":"Prevalence, characteristics, and patterns of patients with multimorbidity in primary care: a retrospective cohort analysis in Canada","abstract":"<jats:sec><jats:title>Background</jats:title><jats:p>Multimorbidity is a complex issue in modern medicine and a more nuanced understanding of how this phenomenon occurs over time is needed.</jats:p></jats:sec><jats:sec><jats:title>Aim</jats:title><jats:p>To determine the prevalence, characteristics, and patterns of patients living with multimorbidity, specifically the unique combinations (unordered patterns) and unique permutations (ordered patterns) of multimorbidity in primary care.</jats:p></jats:sec><jats:sec><jats:title>Design and setting</jats:title><jats:p>A retrospective cohort analysis of the prospectively collected data from 1990 to 2013 from the Canadian Primary Care Sentinel Surveillance Network electronic medical record database.</jats:p></jats:sec><jats:sec><jats:title>Method</jats:title><jats:p>Adult primary care patients who were aged ≥18 years at their first recorded encounter were followed over time. A list of 20 chronic condition categories was used to detect multimorbidity. Computational analyses were conducted using the Multimorbidity Cluster Analysis Tool to identify all combinations and permutations.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Multimorbidity, defined as two or more and three or more chronic conditions, was prevalent among adult primary care patients and most of these patients were aged &lt;65 years. Among female patients with two or more chronic conditions, 6075 combinations and 14 891 permutations were detected. Among male patients with three or more chronic conditions, 4296 combinations and 9716 permutations were detected. While specific patterns were identified, combinations and permutations became increasingly rare as the total number of chronic conditions and patient age increased.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>This research confirms that multimorbidity is common in primary care and provides empirical evidence that clinical management requires a tailored, patient-centred approach. While the prevalence of multimorbidity was found to increase with increasing patient age, the largest proportion of patients with multimorbidity in this study were aged &lt;65 years.</jats:p></jats:sec>","journal":"British Journal of General Practice","year":2019,"id":602133,"datarank":0.5955437870328184,"base_score":3.970291913552122,"endowment":3.970291913552122,"self_citation_contribution":0.5955437870328184,"citation_network_contribution":0.0,"self_endowment_contribution":0.5955437870328184,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":52,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1544188,"name":"Amanda L Terry","orcid":null,"position":1,"is_corresponding":false},{"id":679805,"name":"Martin Fortin","orcid":"0000-0002-9874-3771","position":2,"is_corresponding":false},{"id":1544189,"name":"Tyler Williamson","orcid":null,"position":3,"is_corresponding":false},{"id":854696,"name":"Michael Bauer","orcid":"0000-0003-2498-7295","position":4,"is_corresponding":false},{"id":1544190,"name":"Amardeep Thind","orcid":null,"position":5,"is_corresponding":false},{"id":1544187,"name":"Kathryn Nicholson","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Prevalence, characteristics, and patterns of patients with multimorbidity in primary care: a retrospective cohort analysis in Canada","abstract":"<jats:sec><jats:title>Background</jats:title><jats:p>Multimorbidity is a complex issue in modern medicine and a more nuanced understanding of how this phenomenon occurs over time is needed.</jats:p></jats:sec><jats:sec><jats:title>Aim</jats:title><jats:p>To determine the prevalence, characteristics, and patterns of patients living with multimorbidity, specifically the unique combinations (unordered patterns) and unique permutations (ordered patterns) of multimorbidity in primary care.</jats:p></jats:sec><jats:sec><jats:title>Design and setting</jats:title><jats:p>A retrospective cohort analysis of the prospectively collected data from 1990 to 2013 from the Canadian Primary Care Sentinel Surveillance Network electronic medical record database.</jats:p></jats:sec><jats:sec><jats:title>Method</jats:title><jats:p>Adult primary care patients who were aged ≥18 years at their first recorded encounter were followed over time. A list of 20 chronic condition categories was used to detect multimorbidity. Computational analyses were conducted using the Multimorbidity Cluster Analysis Tool to identify all combinations and permutations.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Multimorbidity, defined as two or more and three or more chronic conditions, was prevalent among adult primary care patients and most of these patients were aged &lt;65 years. Among female patients with two or more chronic conditions, 6075 combinations and 14 891 permutations were detected. Among male patients with three or more chronic conditions, 4296 combinations and 9716 permutations were detected. While specific patterns were identified, combinations and permutations became increasingly rare as the total number of chronic conditions and patient age increased.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>This research confirms that multimorbidity is common in primary care and provides empirical evidence that clinical management requires a tailored, patient-centred approach. 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