Selecting home care quality indicators based on the Resident Assessment Instrument-Home Care (RAI-HC) for Switzerland: A public health and healthcare providers' perspective

Wagner, Aylin; Zúñiga, Franziska; Rüesch, Peter; Schaffert, René; Dratva, Julia

doi:10.1371/journal.pone.0244577

Cited by 9 publications

(5 citation statements)

References 50 publications

(76 reference statements)

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“…A total of 208 articles were retrieved on the initial search, of which 6 articles were presented for review by the expert panel. [10][11][12][13][14][15] The flow chart of the literature search and retrieval is shown in Figure 2. We identified 5 first-level, 20 secondary, and 72 tertiary indicators.…”

Section: Literature Reviewmentioning

confidence: 99%

Construction of Internet +home Care Quality Supervision Indicators in China Based on the Delphi Method

Hou

Peng

et al. 2022

RMHP

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Background With the aging of China’s population, the incidence rate of chronic diseases is rising. At the same time, residents’ health awareness is also increasing. Implementing Internet +home care is an inevitable trend in adapting social development. Currently, Internet +home care is in the pilot stage in China, relevant institutional measures are neither standardized nor perfect, and there is no set of quality supervision indicators (QSIs). Purpose The construction of Internet +home care QSIs in China will provide a theoretical basis for Internet +home care quality supervision. Materials and Methods The Service-Quality model was used as the theoretical framework, and a literature review, semi-structured interviews, focus group discussions, and Delphi consultations determined the contents of the QSIs and the weight of each indicator. Results Internet +home care QSIs were constructed and included 5 first-level indicators, 17 secondary indicators, and 69 tertiary indicators. The effective recovery rates of the two rounds of Delphi expert consultation were 100% and 85%, the expert authority coefficients were 0.810 and 0.833, and the Kendall harmony coefficients were 0.189 and 0.125 (P<0.01). The final set of Internet +home care QSIs was as follows: tangibility (4 secondary and 16 tertiary indicators), reliability (4 secondary and 19 tertiary indicators), guarantee (5 secondary and 20 tertiary indicators), responsiveness (2 secondary and 8 tertiary indicators), and empathy (2 secondary and 6 tertiary indicators). Conclusion The construction of Internet +home care QSIs based on the SERVQUAL model is scientifically valid, and the indicators are reliable. They provide guidance and reference values for the continuous improvement and promotion of Internet +home care. This work also provides a theoretical basis for researching and developing an Internet +home care quality supervision platform.

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Section: Literature Reviewmentioning

confidence: 99%

Construction of Internet +home Care Quality Supervision Indicators in China Based on the Delphi Method

Hou

Peng

et al. 2022

RMHP

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“…Such an approach requires instruments that assess both the health status and the context in which the individual functions. Regarding health and functional status assessment tools, the Resident Assessment Instrument-Home-Care (RAI-HC) [ 19 , 20 ] is frequently used in Swiss home care and contributes to improving the quality of care provided to homecare recipients [ 21 ]. However, there are only a few tools that allow a standardised and comprehensive assessment of the environment.…”

Section: Introductionmentioning

confidence: 99%

Development of a tool to assess environmental factors to support home care – a Delphi study

Schorderet,

Bastiaenen,

de Bie

et al. 2023

BMC Geriatr

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Background Living in an adequate environment suited to one’s abilities and needs is an essential condition to function in daily life. However, no complete tool currently exists to provide a rapid overview of a person’s environment, both material (accommodation and auxiliary means) and social (entourage and available services). Our aim was to develop a tool to identify potentially problematic environmental factors and to determine when an in-depth assessment is necessary. Methods Health professionals experienced in home-based treatment participated in a three-round Delphi process. The first round aimed to define which items the tool should contain, the second to collect participants’ opinions on a first version of the tool, and the third to collect the participants’ opinions on the adapted version of the tool. Results A total of 29 people participated in the first round, 21 in the second and 18 in the third. The final tool contains 205 items divided into four categories (basic information about the inhabitant and their home, inhabitant’s level of independence and autonomy, home, tools and means at the inhabitant’s disposition) and two annexes (stairs to access to the home, internal staircase to the dwelling). Conclusions A complete tool allowing professionals working in patients’ homes to obtain an overview of the environmental factors that could represent obstacles to the independence of the inhabitant, or to the possibility of providing quality care could be developed. This tool is very complete but relatively long. To facilitate its usability, it would be relevant that a digital version to focus on individual relevant categories be elaborated.

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“…The Swiss RAI-HC QIs have so far only been used for internal quality improvement processes. However, in a recent QI evaluation study [ 11 , 12 ], the indicators were examined for their appropriateness for national quality measurement.…”

Section: Introductionmentioning

confidence: 99%

Adjusting Client-Level Risks Impacts on Home Care Organization Ranking

Wagner

Schaffert

Dratva

2021

IJERPH

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Quality indicators (QIs) based on the Resident Assessment Instrument-Home Care (RAI-HC) offer the opportunity to assess home care quality and compare home care organizations’ (HCOs) performance. For fair comparisons, providers’ QI rates must be risk-adjusted to control for different case-mix. The study’s objectives were to develop a risk adjustment model for worsening or onset of urinary incontinence (UI), measured with the RAI-HC QI bladder incontinence, using the database HomeCareData and to assess the impact of risk adjustment on quality rankings of HCOs. Risk factors of UI were identified in the scientific literature, and multivariable logistic regression was used to develop the risk adjustment model. The observed and risk-adjusted QI rates were calculated on organization level, uncertainty addressed by nonparametric bootstrapping. The differences between observed and risk-adjusted QI rates were graphically assessed with a Bland-Altman plot and the impact of risk adjustment examined by HCOs tertile ranking changes. 12,652 clients from 76 Swiss HCOs aged 18 years and older receiving home care between 1 January 2017, and 31 December 2018, were included. Eight risk factors were significantly associated with worsening or onset of UI: older age, female sex, obesity, impairment in cognition, impairment in hygiene, impairment in bathing, unsteady gait, and hospitalization. The adjustment model showed fair discrimination power and had a considerable effect on tertile ranking: 14 (20%) of 70 HCOs shifted to another tertile after risk adjustment. The study showed the importance of risk adjustment for fair comparisons of the quality of UI care between HCOs in Switzerland.

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Selecting home care quality indicators based on the Resident Assessment Instrument-Home Care (RAI-HC) for Switzerland: A public health and healthcare providers' perspective

Cited by 9 publications

References 50 publications

Construction of Internet +home Care Quality Supervision Indicators in China Based on the Delphi Method

Construction of Internet +home Care Quality Supervision Indicators in China Based on the Delphi Method

Development of a tool to assess environmental factors to support home care – a Delphi study

Adjusting Client-Level Risks Impacts on Home Care Organization Ranking

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