Extreme Consumers of Health Care: Patterns of Care Utilization in Patients with Multiple Chronic Conditions Admitted to a Novel Integrated Clinic.
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ABSTRACT: Purpose:Patients with multiple chronic conditions (MCC) of diabetes, cardiovascular and kidney diseases; hereafter referred to as HND (heart/cardiac-, nephrology-, diabetes mellitus-) patients, are high utilizers of health care. However, the care received is often insufficiently coordinated between different specialties and health-care providers. This study aims to describe the characteristics of HND patients and to explore the initial effects of a multidisciplinary and person-centered care on total care utilization. Patients and Methods:We conducted a sub-study of HND patients recruited in an ongoing randomized trial CareHND (NCT03362983). Descriptive statistics of patient characteristics, including diagnostic data and Charlson Comorbidity Index scores, informed a comparison of care utilization patterns between HND patient care and traditional care. Diagnostic and care utilization data were collected from a regional database. Wilcoxon signed ranked sum tests were performed to compare care utilization frequencies between the two groups. Results:Patients included in the study were care-intensive with several diagnoses and experienced a high level of variation in care utilization and diagnoses profiles. HND patients were sicker than their counterparts in the control group. Utilization indicators were similar between the two arms. There was some indication that the HND center is beginning to perform as expected, but no results were statistically significant. Conclusion:This study sits among many studies reporting difficulties obtaining statistically significant findings for MCC patients. However, previous research has shown that the key components of this intervention, such as integrated, multidisciplinary, inter-professional collaboration within patient-centered care have had a positive effect on health-care outcomes. More innovative methods beyond the RCT, such as machine learning should be explored to evaluate the impact of integrated care interventions on care utilization.
SUBMITTER: Rafiq M
PROVIDER: S-EPMC6935286 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
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