Complexity in disease management: A linked data analysis of multimorbidity in Aboriginal and non-Aboriginal patients hospitalised with atherothrombotic disease in Western Australia

Abstract

Background: Hospitalisation for atherothrombotic disease (ATD) is expected to rise in coming decades. However, increasingly, associated comorbidities impose challenges in managing patients and deciding appropriate secondary prevention. We investigated the prevalence and pattern of multimorbidity (presence of two or more chronic conditions) in Aboriginal and non-Aboriginal Western Australian residents with ATDs.

Methods and findings: We used population-based de-identified linked administrative health data from 1 January 2000 to 30 June 2014 to identify a cohort of patients aged 25-59 years admitted to Western Australian hospitals with a discharge diagnosis of ATD. The prevalence of common chronic diseases in these patients was estimated and the patterns of comorbidities and multimorbidities empirically explored using two different approaches: identification of the most commonly occurring pairs and triplets of comorbid diseases, and through latent class analysis (LCA). Half of the cohort had multimorbidity, although this was much higher in Aboriginal people (Aboriginal: 79.2% vs. non-Aboriginal: 39.3%). Only a quarter were without any documented comorbidities. Hypertension, diabetes, alcohol abuse disorders and acid peptic diseases were the leading comorbidities in the major comorbid combinations across both Aboriginal and non-Aboriginal cohorts. The LCA identified four and six distinct clinically meaningful classes of multimorbidity for Aboriginal and non-Aboriginal patients, respectively. Out of the six groups in non-Aboriginal patients, four were similar to the groups identified in Aboriginal patients. The largest proportion of patients (33% in Aboriginal and 66% in non-Aboriginal) was assigned to the "minimally diseased" (or relatively healthy) group, with most patients having less than two conditions. Other groups showed variability in degree and pattern of multimorbidity.

Conclusion: Multimorbidity is common in ATD patients and the comorbidities tend to interact and cluster together. Physicians need to consider these in their clinical practice. Different treatment and secondary prevention strategies are likely to be useful for management in these cluster groups.

Fig 1. Sex stratified distribution of number of morbidities based on different age categories, Aboriginality status and their area of residence.

Fig 2. Characteristics of the multimorbidity disease cluster identified through latent class analysis.

ATDs: Atherothrombotic diseases; SD: Standard deviation; CMG: Cancer-Musculoskeletal-Gastric; VS: Very Sick; DMR: Drug abuse-Mental-Respiratory; MD-Minimally Diseased; CCM: Complex Cardiometabolic.

Fig 3. Predicted probabilities of being in different latent classes according to age of the ATD patients.

Probabilities are adjusted for gender, SEIFA score and level of remoteness. SD: Standard deviation; CMG: Cancer-Musculoskeletal-Gastric; VS: Very Sick; DMR: Drug abuse-Mental-Respiratory; MD-Minimally Diseased; CCM: Complex Cardiometabolic.