TY - JOUR
T1 - Development of a casemix classification to predict costs of home care in the Netherlands
T2 - a study protocol
AU - Elissen, Arianne Mathilda Josephus
AU - Verhoeven, Gertjan Sebastiaan
AU - de Korte, Maud Hortense
AU - van den Bulck, Anne Odilia Emile
AU - Metzelthin, Silke Friederike
AU - van der Weij, Lieuwe Christiaan
AU - Stam, Jaap
AU - Ruwaard, Dirk
AU - Mikkers, Misja Chiljon
N1 - Funding Information:
Funding This work is supported by research grants from the Dutch Healthcare Authority and from home‐care organisation MeanderGroep Zuid‐Limburg, the Netherlands.
Publisher Copyright:
© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2020/2
Y1 - 2020/2
N2 - Introduction Compared 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 analysis The 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 dissemination The 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.
AB - Introduction Compared 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 analysis The 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 dissemination The 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.
KW - INSTRUMENTAL ACTIVITIES
KW - SYSTEM
KW - MODEL
U2 - 10.1136/bmjopen-2019-035683
DO - 10.1136/bmjopen-2019-035683
M3 - Article
C2 - 32071192
SN - 2044-6055
VL - 10
JO - BMJ Open
JF - BMJ Open
IS - 2
M1 - 035683
ER -