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

ABSTRACT:

Background

Case-mix based prospective payment of homecare is being implemented in several countries to work towards more efficient and client-centred homecare. However, existing models can only explain a limited part of variance in homecare use, due to their reliance on health- and function-related client data. It is unclear which predictors could improve predictive power of existing case-mix models. The aim of this study was therefore to identify relevant predictors of homecare use by utilizing the expertise of district nurses and health insurers.

Methods

We conducted a two-round Delphi-study according to the RAND/UCLA Appropriateness Method. In the first round, participants assessed the relevance of eleven client characteristics that are commonly included in existing case-

SUBMITTER: van den Bulck AOE 

PROVIDER: S-EPMC8957197 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature