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Measuring Nursing Home Performance Using Administrative Data

To improve the quality of nursing home care, reliable estimates of outcomes are essential. Obtaining such estimates requires optimal use of limited data, especially for small homes. We analyze the variation in mortality and hospital admissions across nursing homes in the Netherlands during the years...

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Detalles Bibliográficos
Autores principales: Wouterse, Bram, Bakx, Pieter, Wong, Albert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009495/
https://www.ncbi.nlm.nih.gov/pubmed/35872642
http://dx.doi.org/10.1177/10775587221108247
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author Wouterse, Bram
Bakx, Pieter
Wong, Albert
author_facet Wouterse, Bram
Bakx, Pieter
Wong, Albert
author_sort Wouterse, Bram
collection PubMed
description To improve the quality of nursing home care, reliable estimates of outcomes are essential. Obtaining such estimates requires optimal use of limited data, especially for small homes. We analyze the variation in mortality and hospital admissions across nursing homes in the Netherlands during the years 2010–2013. We use administrative data on all nursing home clients. We apply mixed-effects survival models, empirical Bayes estimation, and machine-learning techniques to optimally use the available longitudinal data. We find large differences in both outcomes across nursing homes, yet the estimates are surrounded by substantial uncertainty. We find no correlation between performance on mortality and avoidable hospital admissions, suggesting that these are related to different aspects of quality. Hence, caution is needed when evaluating the performance of individual nursing homes, especially when the number of outcome indicators is limited.
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spelling pubmed-100094952023-03-14 Measuring Nursing Home Performance Using Administrative Data Wouterse, Bram Bakx, Pieter Wong, Albert Med Care Res Rev Empirical Research To improve the quality of nursing home care, reliable estimates of outcomes are essential. Obtaining such estimates requires optimal use of limited data, especially for small homes. We analyze the variation in mortality and hospital admissions across nursing homes in the Netherlands during the years 2010–2013. We use administrative data on all nursing home clients. We apply mixed-effects survival models, empirical Bayes estimation, and machine-learning techniques to optimally use the available longitudinal data. We find large differences in both outcomes across nursing homes, yet the estimates are surrounded by substantial uncertainty. We find no correlation between performance on mortality and avoidable hospital admissions, suggesting that these are related to different aspects of quality. Hence, caution is needed when evaluating the performance of individual nursing homes, especially when the number of outcome indicators is limited. SAGE Publications 2022-07-23 2023-04 /pmc/articles/PMC10009495/ /pubmed/35872642 http://dx.doi.org/10.1177/10775587221108247 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Empirical Research
Wouterse, Bram
Bakx, Pieter
Wong, Albert
Measuring Nursing Home Performance Using Administrative Data
title Measuring Nursing Home Performance Using Administrative Data
title_full Measuring Nursing Home Performance Using Administrative Data
title_fullStr Measuring Nursing Home Performance Using Administrative Data
title_full_unstemmed Measuring Nursing Home Performance Using Administrative Data
title_short Measuring Nursing Home Performance Using Administrative Data
title_sort measuring nursing home performance using administrative data
topic Empirical Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009495/
https://www.ncbi.nlm.nih.gov/pubmed/35872642
http://dx.doi.org/10.1177/10775587221108247
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