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Identifying subgroups of high-need, high-cost, chronically ill patients in primary care: A latent class analysis

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  • Rowan G M Smeets
  • Arianne M J Elissen
  • Mariëlle E A L Kroese
  • Niels Hameleers
  • Dirk Ruwaard

Abstract

Introduction: Segmentation of the high-need, high-cost (HNHC) population is required for reorganizing care to accommodate person-centered, integrated care delivery. Therefore, we aimed to identify and characterize relevant subgroups of the HNHC population in primary care by using demographic, biomedical, and socioeconomic patient characteristics. Methods: This was a retrospective cohort study within a Dutch primary care group, with a follow-up period from September 1, 2014 to August 31, 2017. Chronically ill patients were included in the HNHC population if they belonged to the top 10% of care utilizers and/or suffered from multimorbidity and had an above-average care utilization. In a latent class analysis, forty-one patient characteristics were initially used as potential indicators of heterogeneity in HNHC patients’ needs. Results: Patient data from 12 602 HNHC patients was used. A 4-class model was considered statistically and clinically superior. The classes were named according to the characteristics that were most dominantly present and distinctive between the classes (i.e. mainly age, household position, and source of income). Class 1 (‘older adults living with partner’) included 39.3% of patients, class 2 (‘older adults living alone’) included 25.5% of patients, class 3 (‘middle-aged, employed adults with family’) included 23.3% of patients, and class 4 (‘middle-aged adults with social welfare dependency’) included 11.9% of patients. Diabetes was the most common condition in all classes; the second most prevalent condition differed between osteoarthritis in class 1 (21.7%) and 2 (23.8%), asthma in class 3 (25.3%), and mood disorders in class 4 (23.1%). Furthermore, while general practitioner (GP) care utilization increased during the follow-up period in the classes of older adults, it remained relatively stable in the middle-aged classes. Conclusions: Although the HNHC population is heterogeneous, distinct subgroups with relatively homogeneous patterns of mainly demographic and socioeconomic characteristics can be identified. This calls for tailoring care and increased attention for social determinants of health.

Suggested Citation

  • Rowan G M Smeets & Arianne M J Elissen & Mariëlle E A L Kroese & Niels Hameleers & Dirk Ruwaard, 2020. "Identifying subgroups of high-need, high-cost, chronically ill patients in primary care: A latent class analysis," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-16, January.
    • Handle: RePEc:plo:pone00:0228103
    DOI: 10.1371/journal.pone.0228103
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    1. Vedsted, Peter & Fink, Per & Sørensen, H.T.Henrik Toft & Olesen, Frede, 2004. "Physical, mental and social factors associated with frequent attendance in Danish general practice. A population-based cross-sectional study," Social Science & Medicine, Elsevier, vol. 59(4), pages 813-823, August.
    2. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    3. Liu, Li-Fan & Tian, Wei-Hua & Yao, Hui-Ping, 2012. "Utilization of health care services by elderly people with National Health Insurance in Taiwan: The heterogeneous health profile approach," Health Policy, Elsevier, vol. 108(2), pages 246-255.
    4. Struijs, Jeroen N. & Drewes, Hanneke W. & Heijink, Richard & Baan, Caroline A., 2015. "How to evaluate population management? Transforming the Care Continuum Alliance population health guide toward a broadly applicable analytical framework," Health Policy, Elsevier, vol. 119(4), pages 522-529.
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    1. Rowan G. M. Smeets & Dorijn F. L. Hertroijs & Mariëlle E. A. L. Kroese & Niels Hameleers & Dirk Ruwaard & Arianne M. J. Elissen, 2021. "The Patient Centered Assessment Method (PCAM) for Action-Based Biopsychosocial Evaluation of Patient Needs: Validation and Perceived Value of the Dutch Translation," IJERPH, MDPI, vol. 18(22), pages 1-19, November.
    2. Fluit, Marleen & Bortolotti, Thomas & Broekhuis, Manda & van Teerns, Mayan, 2023. "Segmenting citizens according to their self-sufficiency: A tool for local government," Social Science & Medicine, Elsevier, vol. 335(C).

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