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Canadian Family PhysicianLe Médecin de famille canadien

|

Vol 61: october • octobre 2015

Sentinel Eye | College

Collège

Understanding multimorbidity in primary health care

Kathryn Nicholson

MSc

Amanda L. Terry

PhD

Martin Fortin

MD MSc FCMF

Tyler Williamson

PhD

Amardeep Thind

MD PhD

Q

uantitative and qualitative research has documented the burden of multimorbidity on patients, caregivers, providers, and broader health and social systems in developed countries.1-3 While qualitative research can pro- vide much-needed insight into individual patients, quantita- tive research allows us to examine multimorbidity in large groups. Electronic medical record (EMR) data are key to a population-level, yet clinical, understanding of these com- plex patients. Internationally, EMRs are increasingly form- ing databases of longitudinal, point-of-care information for thousands, even millions, of patients. The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) is currently the only pan-Canadian EMR database. It collects de-identified health information on primary health care (PHC) patients with chronic diseases across the country; these data unite a public health and PHC perspective (point-of-care data combined into a population-level data set).4 CPCSSN EMR data, from more than 1 million patients, are extracted quar- terly and provide real-time insight into PHC patients’ ongo- ing health issues and health care use, holding information not available through population surveys or administrative databases. This uniqueness demands that researchers man- age, analyze, and interpret the data appropriately.

There are specific challenges in multimorbidity research.

First, there is no consensus on how to define multimorbidity;

researchers must adopt a definition that can be populated by EMR data. They must also determine where the data is in the database: problem lists, billing codes, encounter diag- noses, or medications. Validated algorithms to identify true cases of individual chronic diseases within EMR data have been developed5; additional algorithms would provide a starting point for more valid and reliable case identification.

As these data are recorded for clinical not research pur- poses, researchers must consider the effects of missing data on statistical analyses and eventual estimates (eg, diagnos- tic codes might not be recorded at all or might be recorded in non-extracted areas of the EMR). The longitudinal nature of EMR data requires researchers to define the first occur- rence of the chronic diseases that form their multimorbidity definition. It takes time to explore the raw data, understand their quality and completeness, and consider which study designs are most appropriate. For example, multilevel clus- tering of the data (encounters clustered within patients;

patients, within providers; providers, within practices; prac- tices, within networks; and networks, within a province or territory) will require more advanced statistical techniques

or collaboration of clinicians, epidemiologists, biostatisti- cians, and computer scientists. Methodologic decisions dur- ing this process should be clearly articulated, and published in research protocols to enhance the reproducibility and transparency of multimorbidity research.6

Despite these challenges, the CPCSSN database repre- sents a crucial resource for health researchers in Canada.

As EMR functionality evolves, contextual information important for patient-centred care should be recorded and extracted more consistently (eg, employment status, educa- tion, and family structure, as well as patients’ ideas, feelings, and expectations about health) to answer more patient- relevant questions.7 Further, these data can be used to examine effects of interventions and risk-prediction models.

The CPCSSN database continues to be a one-of-a-kind ave- nue to understanding PHC patients living with multimorbid- ity. The CPCSSN database depends on participating practices, sentinels, and patients, and the data provided will allow us to make comparisons with international research exploring the burden of multimorbidity8-10 and contribute our perspec- tive to the growing international knowledge base.

Ms Nicholson is a doctoral candidate in the Department of Epidemiology and Biostatistics in the Schulich School of Medicine & Dentistry at Western University in London, Ont. Dr Terry is Assistant Professor in the Department of Family Medicine and the Centre for Studies in Family Medicine, the Department of Epidemiology and Biostatistics, and the Schulich Interfaculty Program in Public Health in the Schulich School of Medicine & Dentistry. Dr Fortin is Professor in the Department of Family Medicine at Université de Sherbrooke in Quebec and Research Director at the Centre intégré universitaire de santé et de services sociaux du Saguenay–Lac-Saint-Jean.

Dr Williamson is Assistant Professor in the Department of Community Health Sciences and a member of the Alberta Children’s Hospital Research Institute and the O’Brien Institute for Public Health at the University of Calgary in Alberta. Dr Thind holds a Canada Research Chair in Health Services Research and is Professor in the Department of Family Medicine and the Department of Epidemiology and Biostatistics and is Director of the Schulich Interfaculty Program in Public Health.

competing interests None declared Acknowledgment

Funding for this publication was provided by the Public Health Agency of Canada. The views expressed do not necessarily represent the views of the Public Health Agency of Canada.

references

1. Violan C, Foguet-Boreu Q, Flores-Mateo G, Salisbury C, Blom J, Freitag M, et al. Prevalence, determinants and patterns of multimorbidity in primary care: a systematic review of observa- tional studies. PLoS ONE 2014;9(7):e102149-58.

2. Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, et al. Aging with multi- morbidity: a systematic review of the literature. Ageing Res Rev 2011;10:430-9.

3. Prados-Torres A, Calderon-Larranaga A, Hancco-Saavedra J, Poblador-Plou B, van den Akker M. Multimorbidity patterns: a systematic review. J Clin Epidemiol 2014;67:254-66.

4. Birtwhistle RV. Canadian primary care sentinel surveillance network: a developing resource for family medicine and public health. Can Fam Physician 2011;57:1219-20.

5. Williamson T, Green ME, Birtwhistle R, Khan S, Garies S, Wong ST, et al. Validating the 8 CPCSSN case definitions for chronic disease surveillance in a primary care database of elec- tronic health records. Ann Fam Med 2014;12(4):367-72.

6. Smith SM, Mercer SW, Gunn J, van den Akker M, Fortin M. Enhancing research quality and report- ing: why the Journal of Comorbidity is now publishing study protocols. J Comorbidity 2014;4:55-7.

7. Fortin M, Soubhi H, Hudon C, Bayliss EA, van den Akker M. Multimorbidity’s many challenges:

time to focus on the needs of this vulnerable and growing population. BMJ 2007;334:1016-7.

8. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbid- ity and implications for health care, research, and medical education: a cross-sectional study.

Lancet 2012;380(9836):37-43.

9. Prados-Torres A, Poblador-Plou B, Calderon-Larranaga A, Gimeno-Feliu LA, Gonzalez-Rubio F, Poncel-Falco A, et al. Multimorbidity patterns in primary care: interactions among chronic dis- eases using factor analysis. PLoS ONE 2012;7(2):e32190-202.

10. St Sauver JL, Boyd CM, Grossardt BR, Bobo WV, Finney Rutten LJ, Roger VL, et al. Risk of developing multimorbidity across all ages in an historical cohort study: differences by sex and ethnicity. BMJ Open 2015;5:e006413-26.

Sentinel Eye is coordinated by CPCSSN, in partnership with the CFPC, to highlight surveillance and research initiatives related to chronic illness prevalence and management in Canada.

Please send questions or comments to Dr Richard Birtwhistle, Chair, CPCSSN, at richard.birtwhistle@dfm.queensu.ca.

La traduction en français de cet article se trouve à www.cfp.ca dans la table des matières du numéro d’octobre 2015 à la page e489.

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