The Multimorbidity Cluster Analysis Tool: Identifying Combinations and Permutations of Multiple Chronic Diseases Using a Record-Level Computational Analysis

Kathryn Nicholson, Michael Bauer, Amanda Terry, Martin Fortin, Tyler Williamson, Amardeep Thind


Introduction: Multimorbidity, or the co-occurrence of multiple chronic health conditions within an individual, is an increasingly dominant presence and burden in modern health care systems.  To fully capture its complexity, further research is needed to uncover the patterns and consequences of these co-occurring health states.  As such, the Multimorbidity Cluster Analysis Tool and the accompanying Multimorbidity Cluster Analysis Toolkit have been created to allow researchers to identify distinct clusters that exist within a sample of participants or patients living with multimorbidity. 

Development: The Tool and Toolkit were developed at Western University in London, Ontario, Canada.  This open-access computational program (JAVA code and executable file) was developed and tested to support an analysis of thousands of individual records and up to 100 disease diagnoses or categories. 

Application: The computational program can be adapted to the methodological elements of a research project, including type of data, type of chronic disease reporting, measurement of multimorbidity, sample size and research setting.  The computational program will identify all existing, and mutually exclusive, combinations and permutations within the dataset.  An application of this computational program is provided as an example, in which more than 75,000 individual records and 20 chronic disease categories resulted in the detection of 10,411 unique combinations and 24,647 unique permutations among female and male patients. 

Discussion: The Tool and Toolkit are now available for use by researchers interested in exploring the complexities of multimorbidity.  Its careful use, and the comparison between results, will be valuable additions to the nuanced understanding of multimorbidity. 


Multimorbidity, comorbidity, chronic disease, multiple chronic conditions, disease clustering

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Boyd CM, Fortin M. Future of multimorbidity research: how should understanding of multimorbidity inform health system design? Public Health Reviews. 2010;32(2):451-474.

van den Akker M, Buntinx F, Knottnerus AJ. Comorbidity or multimorbidity: what’s in a name? A review of literature. European Journal of General Practice. 1996;2:65-70.

Stewart M, Fortin M, Britt HC, Harrison CM, Maddocks HL. Comparisons of multi-morbidity in family practice - issues and biases. Family Practice. 2013;30:473-480.

Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, et al. Aging with multimorbidity: a systematic review of the literature. Ageing Research Reviews. 2011;10:430-439.

Prados-Torres A, Calderón-Larrañaga A, Hancco-Saavedra J, Poblador-Plou B, van den Akker M. Multimorbidity patterns: a systematic review. Journal of Clinical Epidemiology. 2014;67:254-266.

France EF, Wyke S, Gunn JM, Mair FS, McLean G, Mercer SW. Multimorbidity in primary care: A systematic review of prospective cohort studies. British Journal of General Practice. 2012;62(597):e297-e307.

Harrison C, Britt H, Miller G, Henderson J. Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice. BMJ Open. 2014;4:e004694-e004703.

Duguay C, Gallagher F, Fortin M. The experience of adults with multimorbidity: a qualitative study. Journal of Comorbidity. 2014;4:11-21.

Smith S, O’Dowd T. Chronic diseases: what happens when they come in multiples? British Journal of General Practice. 2007;57(537):268-270.

Gill A, Kuluski K, Jaakkimainen L, Naganathan G, Upshur R, Wodchis WP. “Where do we go from here?” Health system frustrations expressed by patients with multimorbidity, their caregivers and family physicians. Healthcare Policy. 2014;9(4):73-89.

Morris RL, Sanders C, Kennedy AP, Rogers A. Shifting priorities in multimorbidity: a longitudinal qualitative study of patient’s prioritization of multiple conditions. Chronic Illness. 2011;7(2):147-161.

Pefoyo AJK, Bronskill SE, Gruneir A, Calzavara A, Thavorn K, Petrosyan Y, et al. The increasing burden and complexity of multimorbidity. BMC Public Health. 2015;15:415-26.

Tinetti ME, Basu J. Research on multiple chronic conditions: where we are and where we need to go. Medical Care. 2014;52(3):s3-6.

Mercer SW, Smith SM, Wyke S, O’Dowd T, Watt GC. Multimorbidity in primary care: developing the research agenda. Family Practice. 2009;26(2):79-80

Fortin M, Stewart M, Poitras M-E, Almirall J, Maddocks H. A systematic review of prevalence studies on multimorbidity: toward a more uniform methodology. Annals of Family Medicine. 2012;10(2):142-151.

CPCSSN. Canadian Primary Care Sentinel Surveillance Network. 2016. Available from:

Nicholson K, Terry AL, Fortin M, Williamson T, Bauer M, Thind A. Examining the prevalence and patterns of multimorbidity in Canadian primary healthcare: a methodologic protocol using a national electronic medical record database. Journal of Comorbidity. 2015;5:150-161.



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