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Development and Validation of a Prediction Model for 6-Month Societal Costs in Older Community Care-Recipients in Multiple Countries; the IBenC Study

  • Lisanne I. van Lier*
  • , Judith E. Bosmans
  • , Henriëtte G. van der Roest
  • , Martijn W. Heymans
  • , Vjenka Garms-Homolová
  • , Anja Declercq
  • , Pálmi V Jónsson
  • , Hein P.J. van Hout
  • *Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

This study aims to develop and validate a prediction model of societal costs during a period of 6-months in older community care-recipients across multiple European countries. Participants were older community care-recipients from 5 European countries. The outcome measure was mean 6-months total societal costs of resource utilisation (healthcare and informal care). Potential predictors included sociodemographic characteristics, functional limitations, clinical conditions, and diseases/disorders. The model was developed by performing Linear Mixed Models with a random intercept for the effect of country and validated by an internal-external validation procedure. Living alone, caregiver distress, (I)ADL impairment, required level of care support, health instability, presence of pain, behavioural problems, urinary incontinence and multimorbidity significantly predicted societal costs during 6 months. The model explained 32% of the variation within societal costs and showed good calibration in Iceland, Finland and Germany. Minor model adaptations improved model performance in The Netherland and Italy. The results can provide a valuable orientation for policymakers to better understand cost development among older community care-recipients. Despite substantial differences of countries’ care systems, a validated cross-national set of key predictors could be identified.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalHealth Services Insights
Volume13
DOIs
Publication statusPublished - 1 Jan 2020

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: The IBenC study is funded by the 7th Framework Programme of the European Commission (grant number 305912).

FundersFunder number
7th Framework Programme of the European Commission
European Commission305912

    Keywords

    • elderly people
    • Linear Mixed Models
    • Prediction model
    • societal costs

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