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      The Impact of Wages on Care Home Quality in England

      research-article
      , PhD , , PhD
      , PhD, FGSA
      The Gerontologist
      Oxford University Press
      Care homes, Long-term care, Nursing homes, Service ratings, Staff

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          Abstract

          Background and Objectives

          In many countries, a large proportion of long-term care staff are paid at, or near, minimum wage, leading to concerns of negative effects on care outcomes. This study analyzed the effect of staff wages on care home quality ratings in England.

          Research Design and Methods

          A national staffing database of long-term care providers was matched with local-area information on needs and supply to construct a 3-year panel (2016–2018) of English care home observations. Using multiple imputation methods to address missing data provided a data set of 12,055 observations of 5,556 care facilities (both residential and nursing homes). We analyzed the effect of the facility-level average hourly wage of care staff on national regulator quality ratings. A measure of the impact of exogenous changes in the national minimum wage on care facilities was used as an instrument for wage.

          Results

          We find that wages positively affect care home quality ratings. Other things equal, a 10% increase in the average hourly wage of direct care workers would lead to a 7.1% increase in the likelihood that a care home will have a high-quality rating. The wage effect on quality was significant when controlling for staff skill mix, measured as the share of registered nurses in nursing home staff.

          Discussion and Implications

          This study provides important evidence of the positive impact that staff pay can have on the quality of long-term care. Our finding has important implications for appropriate levels of pay and the funding of long-term care.

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          Most cited references66

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          Multiple imputation using chained equations: Issues and guidance for practice

          Multiple imputation by chained equations is a flexible and practical approach to handling missing data. We describe the principles of the method and show how to impute categorical and quantitative variables, including skewed variables. We give guidance on how to specify the imputation model and how many imputations are needed. We describe the practical analysis of multiply imputed data, including model building and model checking. We stress the limitations of the method and discuss the possible pitfalls. We illustrate the ideas using a data set in mental health, giving Stata code fragments. 2010 John Wiley & Sons, Ltd.
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            The quality of care. How can it be assessed?

            Before assessment can begin we must decide how quality is to be defined and that depends on whether one assesses only the performance of practitioners or also the contributions of patients and of the health care system; on how broadly health and responsibility for health are defined; on whether the maximally effective or optimally effective care is sought; and on whether individual or social preferences define the optimum. We also need detailed information about the causal linkages among the structural attributes of the settings in which care occurs, the processes of care, and the outcomes of care. Specifying the components or outcomes of care to be sampled, formulating the appropriate criteria and standards, and obtaining the necessary information are the steps that follow. Though we know much about assessing quality, much remains to be known.
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              On the Pooling of Time Series and Cross Section Data

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                Author and article information

                Contributors
                Role: Decision Editor
                Journal
                Gerontologist
                Gerontologist
                geront
                The Gerontologist
                Oxford University Press (US )
                0016-9013
                1758-5341
                November 2023
                25 March 2023
                25 March 2023
                : 63
                : 9
                : 1428-1436
                Affiliations
                Personal Social Services Research Unit (PSSRU), University of Kent , Canterbury, UK
                Personal Social Services Research Unit (PSSRU), University of Kent , Canterbury, UK
                Author notes
                Address correspondence to: Stephen Allan, PhD, Personal Social Services Research Unit (PSSRU), University of Kent, CC205, Cornwallis Building, Canterbury, CT2 7NZ, UK. E-mail: S.Allan@ 123456kent.ac.uk
                Author information
                https://orcid.org/0000-0002-1208-9837
                https://orcid.org/0000-0001-7882-3400
                Article
                gnad032
                10.1093/geront/gnad032
                10581380
                36964753
                ee285be9-5b36-4650-898b-0d5f84e1f9bc
                © The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 01 July 2022
                : 23 February 2023
                : 07 August 2023
                Page count
                Pages: 9
                Funding
                Funded by: National Institute for Health and Care Research, DOI 10.13039/501100000272;
                Award ID: 15/144/51
                Funded by: Health Services and Delivery Research Programme, DOI 10.13039/501100002001;
                Award ID: 15/144/51
                Categories
                Quality of Care
                AcademicSubjects/SOC02600

                Geriatric medicine
                care homes,long-term care,nursing homes,service ratings,staff
                Geriatric medicine
                care homes, long-term care, nursing homes, service ratings, staff

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