Population stratification based on healthcare trajectories: A method for encouraging adaptive learning at meso level.

Autor: Lambert AS; Institute of Health and Society (IRSS), Catholic University of Louvain, Brussels, Belgium. Electronic address: anne-sophie.lambert@uclouvain.be., Legrand C; Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA-LIDAM), Catholic University of Louvain, Louvain-la-Neuve, Belgium., Scholtes B; Research Unit of Primary Care and Health, General Practice Department, University of Liège, Liège, Belgium., Samadoulougou S; Institute of Health and Society (IRSS), Catholic University of Louvain, Brussels, Belgium., Deconinck H; Institute of Health and Society (IRSS), Catholic University of Louvain, Brussels, Belgium., Alvarez L; Institute of Health and Society (IRSS), Catholic University of Louvain, Brussels, Belgium., Macq J; Institute of Health and Society (IRSS), Catholic University of Louvain, Brussels, Belgium.
Jazyk: angličtina
Zdroj: Health policy (Amsterdam, Netherlands) [Health Policy] 2024 Oct; Vol. 148, pp. 105137. Date of Electronic Publication: 2024 Jul 29.
DOI: 10.1016/j.healthpol.2024.105137
Abstrakt: This paper proposes a method to support population management by evaluating population needs using population stratification based on healthcare trajectories. Reimbursed healthcare consumption data for the first semester of 2017 contained within the inter-mutualist database were analysed to create healthcare trajectories for a subset of the population aged between 60 and 79 (N = 22,832) to identify (1) the nature of health events, (2) key transitions between lines of care, (3) the relative duration of different events, and (4) the hierarchy of events. These factors were classified using a K-mers approach followed by multinomial mixture modelling. Five population groups were identified using this healthcare trajectory approach: "low users", "high intensity of nursing care", "transitional care & nursing care", "transitional care", and "long time in hospital". This method could be used by loco-regional governing bodies to learn reflectively from the place where care is provided, taking a systems perspective rather than a disease perspective, and avoiding the one-size-fits-all definition. It invites decision makers to make better use of routinely collected data to guide continuous learning and adaptive management of population health needs.
(Copyright © 2024. Published by Elsevier B.V.)
Databáze: MEDLINE
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