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, Henriette G. van der Roest, Martijn W. Heymans, Vjenka Garms-Homolova, Anja Declercq, Palmi Jonsson, Hein P. J. van Hout

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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
Publication statusPublished - Dec 2020


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

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