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. 2018 Dec 17;13(12):e0208875.
doi: 10.1371/journal.pone.0208875. eCollection 2018.

Multimorbidity patterns in high-need, high-cost elderly patients

Alessandra Buja  1 , Mirko Claus  1 , Lucia Perin  2 , Michele Rivera  3 , Maria Chiara Corti  4 , Francesco Avossa  4 , Elena Schievano  4 , Stefano Rigon  4 , Roberto Toffanin  4 , Vincenzo Baldo  1 , Giovanna Boccuzzo  2
Affiliations

Multimorbidity patterns in high-need, high-cost elderly patients

Alessandra Buja et al. PLoS One. .

Abstract

Introduction: Patients with complex health care needs (PCHCN) are individuals who require numerous, costly care services and have been shown to place a heavy burden on health care resources. It has been argued that an important issue in providing value-based primary care concerns how to identify groups of patients with similar needs (who pose similar challenges) so that care teams and care delivery processes can be tailored to each patient subgroup. Our study aims to describe the most common chronic conditions and their combinations in a cohort of elderly PCHCN.

Methods: We focused on a cohort of PCHCN residing in an area served by a local public health unit (the "Azienda ULSS4-Veneto") and belonging to Resource Utilization Bands 4 and 5 according to the ACG System. For each patient we extracted Expanded Diagnosis Clusters, and combined them with information available from Rx-MGs diagnoses. For the present work we focused on 15 diseases/disorders, analyzing their combinations as dyads and triads. Latent class analysis was used to elucidate the patterns of the morbidities considered in the PCHCN.

Results: Five disease clusters were identified: one concerned metabolic-ischemic heart diseases; one was labelled as neurological and mental disorders; one mainly comprised cardiac diseases such as congestive heart failure and atrial fibrillation; one was largely associated with respiratory conditions; and one involved neoplasms.

Conclusions: Our study showed specific common associations between certain chronic diseases, shedding light on the patterns of multimorbidity often seen in PCHCN. Studying these patterns in more depth may help to better organize the intervention needed to deal with these patients.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Number of chronic disorders by age group.
Fig 2
Fig 2. Bubble chart.
(a) Bubble chart for the prevalences observed. A larger bubble indicates a higher observed prevalence of the dyad. (b) Bubble chart for the associations between chronic diseases, measured with the chi2 statistic. A larger bubble indicates a stronger association between the diseases. CAN = cancer; CHD = coronary heart disease; AD = Alzheimer’s disease; CVD = cerebrovascular disease; DM = diabetes mellitus; HBP = high blood pressure; HF = heart failure; COPD = chronic obstructive pulmonary disease; CKD = chronic kidney disease; DD = depressive disorder; AF = atrial fibrillation; ASTH = asthma; OP = osteoporosis; HT = hypothyroidism; HL = hyperlipidemia.
Fig 3
Fig 3. Dendrogram for hierarchical cluster analysis by disease.
CAN = cancer; CHD = coronary heart disease; AD = Alzheimer’s disease; CVD = cerebrovascular disease; DM = diabetes mellitus; HBP = high blood pressure; HF = heart failure; COPD = chronic obstructive pulmonary disease; CKD = chronic kidney disease; DD = depressive disorder; AF = atrial fibrillation; ASTH = asthma; OP = osteoporosis; HT = hypothyroidism; HL = hyperlipidemia.
See this image and copyright information in PMC

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