Development of a casemix classification to predict costs of home care in the Netherlands: a study protocol

Abstract

IntroductionCompared with fee-for-service systems, prospective payment based on casemix classification is thought to promote more efficient, needs-based care provision. We aim to develop a casemix classification to predict the costs of home care in the Netherlands.Methods and analysisThe research is designed as a multicentre, cross-sectional cohort study using quantitative methods to identify the relative cost predictors of home care and combine these into a casemix classification, based on individual episodes of care. The dependent variable in the analyses is the cost of home care utilisation, which is operationalised through various measures of formal and informal care, weighted by the relative wage rates of staff categories. As independent variables, we will use data from a recently developed Casemix Short-Form questionnaire, combined with client information from participating home care providers’ (nursing) classification systems and data on demographics and care category (ie, a classification mandated by health insurers). Cost predictors are identified using random forest variable importance measures, and then used to build regression tree models. The casemix classification will consist of the leaves of the (pruned) regression tree. Internal validation is addressed by using cross-validation at various stages of the modelling pathways. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis statement was used to prepare this study protocol.Ethics and disseminationThe study was classified by an accredited Medical Research Ethics Committee as not subject to the Dutch Medical Research Involving Human Subjects Act. Findings are expected in 2020 and will serve as input for the development of a new payment system for home care in the Netherlands, to be implemented at the discretion of the Dutch Ministry of Health, Welfare and Sports. The results will also be published in peer-reviewed publications and policy briefs, and presented at (inter)national conferences.

In the Eye of the Storm: A Quantitative and Qualitative Account of the Impact of the COVID-19 Pandemic on Dutch Home Healthcare

“…Four Dutch HHC organizations participated in this study. They were selected based on their participation in a pilot study conducted previously regarding the development of case-mix classification for HHC in the Netherlands [ 13 ]. The selected HHC organizations operate in various regions of the Netherlands and provide services to relatively large client populations (i.e., about 2000–4000 clients per organization at any given time).…”

Identifying client characteristics to predict homecare use more accurately: a Delphi-study involving nurses and homecare purchasing specialists

“…The researchers involved in this selection have expertise in the areas of (home care) nursing, primary care, health policy and health economics. We selected characteristics that: 1) were known predictors of homecare use in the literature; 2) involved a predictor category that had not yet been included in the CM-SF questionnaire; or 3) were identified as lacking in the CM-SF questionnaire by (among others) district nurses in the pilot-study [ 3 , 17 ]. Suggestions that overlapped with items already in the CM-SF questionnaire or for which no definition was provided were excluded.…”

“…Examples of case-mix models are the Home and Community Services Support Case-Mix (HCSS CM) model in New Zealand, which is based on the International Resident Assessment Instrument for Homecare (InterRAI-HC) data [ 1 ]. Most recently, in the Netherlands a case-mix model has been developed for Dutch homecare, based on Case-Mix Short Form (CM-SF) questionnaire data (Van den Bulck AOE, Elissen AMJ, Metzelthin SF, de Korte MH, Verhoeven GS, Mikkers MC, Ruwaard D. The Case-Mix Short-Form questionnaire for prospective payment of homecare services: Development and psychometric testing, Under review) [ 3 ].…”

“…between 14 and 21% for newly developed models) [ 4 ]. Including other types of predictors could potentially improve the predictive value of case-mix models in homecare [ 3 ]. In a more recent study on predictors of homecare use, it was described that people in need for homecare are generally older, visit the general practitioner more often, and use more and/or expensive medications and aid devices [ 5 ].…”

Integrating Services for Older People in Lithuania

“…Swedish municipalities must report their data on some quality indicators, which are made public in Open Comparisons (Public health agency of Sweden, 2022 [20]). The figures are easy to read, with traffic-light colours indicating performances (green-yellow-red) (Trygged, 2017 [21]). In England, the Care Quality Commission carries out inspections and issue ratings for care providers and it is also in the process of expanding the scope of their assessments to include local authorities themselves as part of an ongoing reform.…”