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Tailoring integrated care services for high-risk patients with multiple chronic conditions: a risk stratification approach using cluster analysis.

ABSTRACT: BACKGROUND:The purpose of this study was to produce a risk stratification within a population of high-risk patients with multiple chronic conditions who are currently treated under a case management program and to explore the existence of different risk subgroups. Different care strategies were then suggested for healthcare reform according to the characteristics of each subgroup. METHODS:All high-risk multimorbid patients from a case management program in the Navarra region of Spain were included in the study (n?=?885). A 1-year mortality risk score was estimated for each patient by logistic regression. The population was then divided into subgroups according to the patients' estimated risk scores. We used cluster analysis to produce the stratification with Ward's linkage hierarchical algorithm. The characteristics of the resulting subgroups were analyzed, and post hoc pairwise tests were performed. RESULTS:Three distinct risk strata were found, containing 45, 38 and 17% of patients. Age increased from cluster to cluster, and functional status, clinical severity, nursing needs and nutritional values deteriorated. Patients in cluster 1 had lower renal deterioration values, and patients in cluster 3 had higher rates of pressure skin ulcers, higher rates of cerebrovascular disease and dementia, and lower prevalence rates of chronic obstructive pulmonary disease. CONCLUSIONS:This study demonstrates the existence of distinct subgroups within a population of high-risk patients with multiple chronic conditions. Current case management integrated care programs use a uniform treatment strategy for patients who have diverse needs. Alternative treatment strategies should be considered to fit the needs of each patient subgroup.

SUBMITTER: Bretos-Azcona PE

PROVIDER: S-EPMC7451239 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Tailoring integrated care services for high-risk patients with multiple chronic conditions: a risk stratification approach using cluster analysis.

Bretos-Azcona Pablo E PE Sánchez-Iriso Eduardo E Cabasés Hita Juan M JM

BMC health services research 20200827 1

<h4>Background</h4>The purpose of this study was to produce a risk stratification within a population of high-risk patients with multiple chronic conditions who are currently treated under a case management program and to explore the existence of different risk subgroups. Different care strategies were then suggested for healthcare reform according to the characteristics of each subgroup.<h4>Methods</h4>All high-risk multimorbid patients from a case management program in the Navarra region of Sp ...[more]

PMID: 32854694

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Project description:BackgroundApproximately 28% of adults have ≥3 chronic conditions (CCs), accounting for two-thirds of U.S. healthcare costs, and often having suboptimal outcomes. Despite Institute of Medicine recommendations in 2001 to integrate guidelines for multiple CCs, progress is minimal. The vast number of unique combinations of CCs may limit progress.Methods and findingsTo determine whether major CCs segregate differentially in limited groups, electronic health record and Medicare paid claims data were examined in one accountable care organization with 44,645 Medicare beneficiaries continuously enrolled throughout 2015. CCs predicting clinical outcomes were obtained from diagnostic codes. Agglomerative hierarchical clustering defined 13 groups having similar within group patterns of CCs and named for the most common CC. Two groups, congestive heart failure (CHF) and kidney disease (CKD), included 23% of beneficiaries with a very high CC burden (10.5 and 8.1 CCs/beneficiary, respectively). Five groups with 54% of beneficiaries had a high CC burden ranging from 7.1 to 5.9 (descending order: neurological, diabetes, cancer, cardiovascular, chronic pulmonary). Six groups with 23% of beneficiaries had an intermediate-low CC burden ranging from 4.7 to 0.4 (behavioral health, obesity, osteoarthritis, hypertension, hyperlipidemia, 'other'). Hypertension and hyperlipidemia were common across groups, whereas 80% of CHF segregated to the CHF group, 85% of CKD to CKD and CHF groups, 82% of cancer to Cancer, CHF, and CKD groups, and 85% of neurological disorders to Neuro, CHF, and CKD groups. Behavioral health diagnoses were common only in groups with a high CC burden. The number of CCs/beneficiary explained 36% of the variance (R2 = 0.36) in claims paid/beneficiary.ConclusionsIdentifying a limited number of groups with high burdens of CCs that disproportionately drive costs may help inform a practical number of integrated guidelines and resources required for comprehensive management. Cluster informed guideline integration may improve care quality and outcomes, while reducing costs.

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Tailoring integrated care services for high-risk patients with multiple chronic conditions: a risk stratification approach using cluster analysis.

Publications

Tailoring integrated care services for high-risk patients with multiple chronic conditions: a risk stratification approach using cluster analysis.

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