van den Bulck AOE, Metzelthin SF, Elissen AMJ, Stadlander MC, Stam JE, Wallinga G, Ruwaard D. Which client characteristics predict home-care needs? Results of a survey study among Dutch home-care nurses.
Health Soc Care Community 2019;
27:93-104. [PMID:
30027552 PMCID:
PMC7379651 DOI:
10.1111/hsc.12611]
[Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 06/07/2018] [Accepted: 06/12/2018] [Indexed: 06/08/2023]
Abstract
Fee-for-service, funding care on an hourly rate basis, creates an incentive for home-care providers to deliver high amounts of care. Under casemix funding, in contrast, clients are allocated-based on their characteristics-to homogenous, hierarchical groups, which are subsequently funded to promote more effective and efficient care. The first step in developing a casemix model is to understand which client characteristics are potential predictors of home-care needs. Nurses working in home care (i.e. home-care nurses) have a good insight into clients' home-care needs. This study was conducted in co-operation with the Dutch Nurses' Association and the Dutch Healthcare Authority. Based on international literature, 35 client characteristics were identified as potential predictors of home-care needs. In an online survey (May, 2017), Dutch home-care nurses were asked to score these characteristics on relevance, using a 9-point Likert scale. They were subsequently asked to identify the top five client characteristics. Data were analysed using descriptive statistics. The survey was completed by 1,007 home-care nurses. Consensus on relevance was achieved for 15 client characteristics, with "terminal phase" being scored most relevant, and "sex" being scored as the least relevant. Relevance of the remaining 20 characteristics was uncertain. Additionally, based on the ranking, "ADL functioning" was ranked as most relevant. According to home-care nurses, both biomedical and psychosocial client characteristics need to be taken into account when predicting home-care needs. Collaboration between clinical practice, policy development, and science is necessary to realise a funding model, to work towards the Triple Aim (improved health, better care experience, and lower costs).
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