Quality of care in European home care programs using the second generation interRAI Home Care Quality Indicators (HCQIs)

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Abstract

Background

Evaluating the quality of care provided to older individuals is a key step to ensure that needs are being met and to target interventions to improve care. To this aim, interRAI’s second-generation home care quality indicators (HCQIs) were developed in 2013. This study assesses the quality of home care services in six European countries using these HCQIs as well as the two derived summary scales.

Methods

Data for this study were derived from the Aged in Home Care (AdHOC) study - a cohort study that examined different models of community care in European countries. The current study selected a sub-sample of the AdHOC cohort from six countries whose follow-up data were complete (Czech Republic, Denmark, Finland, Germany, Italy and the Netherlands). Data were collected from the interRAI Home Care instrument (RAI-HC) between 2000 and 2002. The 23 HCQIs of interest were determined according to previously established methodology, including risk adjustment. Two summary measures, the Clinical Balance Scale and Independence Quality Scale were also determined using established methodology.

Results

A total of 1,354 individuals from the AdHOC study were included in these analyses. Of the 23 HCQIs that were measured, the highest proportion of individuals experienced declines in Instrumental Activities of Daily Living (IADLs) (48.4 %). Of the clinical quality indicators, mood decline was the most prevalent (30.0 %), while no flu vaccination and being alone and distressed were the most prevalent procedural and social quality indicators, respectively (33.4 and 12.8 %). Scores on the two summary scales varied by country, but were concentrated around the median mark.

Conclusions

The interRAI HCQIs can be used to determine the quality of home care services in Europe and identify areas for improvement. Our results suggest functional declines may prove the most beneficial targets for interventions.

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Most cited references 18

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MDS Cognitive Performance Scale.

J N Morris, B E Fries, D. Mehr … (1994)

Chronic cognitive impairment is a major problem in U.S. nursing homes, yet traditional assessment systems in most facilities included only limited information on cognitive status. Following the Congressional mandate in the Omnibus Reconciliation Act of 1987 (OBRA '87), U.S. nursing homes now complete the Minimum Data Set (MDS), a standardized, comprehensive assessment of each resident's functional, medical, psychosocial, and cognitive status. We designed a Cognitive Performance Scale (CPS) that uses MDS data to assign residents into easily understood cognitive performance categories. Information was drawn from three data sets, including two multistate data sets constructed for the Health Care Financing Administration. The prevalence and reliability of the MDS cognitive performance variables were established when assessed by trained nursing personnel. Five selected MDS items were combined to create the single, functionally meaningful seven-category hierarchical Cognitive Performance Scale. The CPS scale corresponded closely with scores generated by the Mini-Mental State Examination and the Test for Severe Impairment, nursing judgments of disorientation, and neurological diagnoses of Alzheimer's disease and other dementias. The new CPS provides a functional view of cognitive performance, using readily available MDS data. It should prove useful to clinicians and investigators using the MDS to determine a resident's cognitive assets.

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Development of a minimum data set-based depression rating scale for use in nursing homes.

A B Burrows, J N Morris, S E Simon … (2000)

depression is common but under-diagnosed in nursing-home residents. There is a need for a standardized screening instrument which incorporates daily observations of nursing-home staff. to develop and validate a screening instrument for depression using items from the Minimum Data Set of the Resident Assessment Instrument. we conducted semi-structured interviews with 108 residents from two nursing homes to obtain depression ratings using the 17-item Hamilton Depression Rating Scale and the Cornell Scale for Depression in Dementia. Nursing staff completed Minimum Data Set assessments. In a randomly assigned derivation sample (n = 81), we identified Minimum Data Set mood items that were correlated (P < 0.05) with Hamilton and Cornell ratings. These items were factored using an oblique rotation to yield five conceptually distinct factors. Using linear regression, each set of factored items was regressed against Hamilton and Cornell ratings to identify a core set of seven Minimum Data Set mood items which comprise the Minimum Data Set Depression Rating Scale. We then tested the performance of the Minimum Data Set Depression Rating Scale against accepted cut-offs and psychiatric diagnoses. a cutpoint score of 3 on the Minimum Data Set Depression Rating Scale maximized sensitivity (94% for Hamilton, 78% for Cornell) with minimal loss of specificity (72% for Hamilton, 77% for Cornell) when tested against cut-offs for mild to moderate depression in the derivation sample. Results were similar in the validation sample. When tested against diagnoses of major or non-major depression in a subset of 82 subjects, sensitivity was 91% and specificity was 69%. Performance compared favourably with the 15-item Geriatric Depression Scale. items from the Minimum Data Set can be organized to screen for depression in nursing-home residents. Further testing of the instrument is now needed.

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Comprehensive clinical assessment in community setting: applicability of the MDS-HC.

J. D. Morris, J. Hirdes, R Gilgen … (1997)

To describe the results of an international trial of the home care version of the MDS assessment and problem identification system (the MDS-HC), including reliability estimates, a comparison of MDS-HC reliabilities with reliabilities of the same items in the MDS 2.0 nursing home assessment instrument, and an examination of the types of problems found in home care clients using the MDS-HC. Independent, dual assessment of clients of home-care agencies by trained clinicians using a draft of the MDS-HC, with additional descriptive data regarding problem profiles for home care clients. Reliability data from dual assessments of 241 randomly selected clients of home care agencies in five countries, all of whom volunteered to test the MDS-HC. Also included are an expanded sample of 780 home care assessments from these countries and 187 dually assessed residents from 21 nursing homes in the United States. The array of MDS-HC assessment items included measures in the following areas: personal items, cognitive patterns, communication/hearing, vision, mood and behavior, social functioning, informal support services, physical functioning, continence, disease diagnoses health conditions and preventive health measures, nutrition/hydration, dental status, skin condition, environmental assessment, service utilization, and medications. Forty-seven percent of the functional, health status, social environment, and service items in the MDS-HC were taken from the MDS 2.0 for nursing homes. For this item set, it is estimated that the average weighted Kappa is .74 for the MDS-HC and .75 for the MDS 2.0. Similarly, high reliability values were found for items newly introduced in the MDS-HC (weighted Kappa = .70). Descriptive findings also characterize the problems of home care clients, with subanalyses within cognitive performance levels. Findings indicate that the core set of items in the MDS 2.0 work equally well in community and nursing home settings. New items are highly reliable. In tandem, these instruments can be used within the international community, assisting and planning care for older adults within a broad spectrum of service settings, including nursing homes and home care programs. With this community-based, second-generation problem and care plan-driven assessment instrument, disability assessment can be performed consistently across the world.

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Author and article information

Contributors

Andrea D. Foebel: andrea.foebel@ki.se

Hein P. van Hout: hpj.vanhout@vumc.nl

Henriëtte G. van der Roest: hg.vanderroest@vumc.nl

Eva Topinkova: eva.topinkova@vfn.cz

Vjenka Garms-Homolova: garmsho@htw-berlin.de

Dinnus Frijters: d.frijters@vumc.nl

Harriet Finne-Soveri: harriet.finne-soveri@thl.fi

Pálmi V. Jónsson: palmivj@landspitali.is

John P. Hirdes: hirdes@uwaterloo.ca

Roberto Bernabei: roberto.bernabei@rm.unicatt.it

Graziano Onder: graziano.onder@rm.unicatt.it

Journal

Journal ID (nlm-ta): BMC Geriatr

Journal ID (iso-abbrev): BMC Geriatr

Title: BMC Geriatrics

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2318

Publication date (Electronic): 14 November 2015

Publication date PMC-release: 14 November 2015

Publication date Collection: 2015

Volume: 15

Electronic Location Identifier: 148

Affiliations

[ ]Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden

[ ]Department of Geriatrics, Neuroscience and Orthopedics, Catholic University, Rome, Italy

[ ]Department of General Practice and Elderly Care Medicine, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands

[ ]Department of Geriatrics, First Faculty of Medicine, Charles University, Prague, Czech Republic

[ ]HTW Berlin, University of Applied Sciences in Technology and Economics, Berlin, Germany

[ ]National Institute for Health and Welfare, Helsinki, Finland

[ ]Department of Geriatrics, Faculty of Medicine, University of Iceland, Reykjavik, Iceland

[ ]School of Public Health and Health Systems, University of Waterloo, Waterloo, ON Canada

Article

Publisher ID: 146

DOI: 10.1186/s12877-015-0146-5

PMC ID: 4647796

PubMed ID: 26572734

SO-VID: 003f579d-5601-4f2e-8aeb-90a373f565b7

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 26 June 2015

Date accepted : 10 November 2015

Custom metadata

ScienceOpen disciplines: Geriatric medicine

Keywords: home care,interrai,assessment,quality indicators,performance measurement

Data availability:

ScienceOpen disciplines: Geriatric medicine

Keywords: home care, interrai, assessment, quality indicators, performance measurement

Quality of care in European home care programs using the second generation interRAI Home Care Quality Indicators (HCQIs)

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Most cited references 18

MDS Cognitive Performance Scale.

Development of a minimum data set-based depression rating scale for use in nursing homes.

Comprehensive clinical assessment in community setting: applicability of the MDS-HC.

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