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The profile inter‐unit reliability

To assess the quality of health care, patient outcomes associated with medical providers (eg, dialysis facilities) are routinely monitored in order to identify poor (or excellent) provider performance. Given the high stakes of such evaluations for payment as well as public reporting of quality, it i...

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Autores principales: He, Kevin, Dahlerus, Claudia, Xia, Lu, Li, Yanming, Kalbfleisch, John D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318309/
https://www.ncbi.nlm.nih.gov/pubmed/31642521
http://dx.doi.org/10.1111/biom.13167
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author He, Kevin
Dahlerus, Claudia
Xia, Lu
Li, Yanming
Kalbfleisch, John D.
author_facet He, Kevin
Dahlerus, Claudia
Xia, Lu
Li, Yanming
Kalbfleisch, John D.
author_sort He, Kevin
collection PubMed
description To assess the quality of health care, patient outcomes associated with medical providers (eg, dialysis facilities) are routinely monitored in order to identify poor (or excellent) provider performance. Given the high stakes of such evaluations for payment as well as public reporting of quality, it is important to assess the reliability of quality measures. A commonly used metric is the inter‐unit reliability (IUR), which is the proportion of variation in the measure that comes from inter‐provider differences. Despite its wide use, however, the size of the IUR has little to do with the usefulness of the measure for profiling extreme outcomes. A large IUR can signal the need for further risk adjustment to account for differences between patients treated by different providers, while even measures with an IUR close to zero can be useful for identifying extreme providers. To address these limitations, we propose an alternative measure of reliability, which assesses more directly the value of a quality measure in identifying (or profiling) providers with extreme outcomes. The resulting metric reflects the extent to which the profiling status is consistent over repeated measurements. We use national dialysis data to examine this approach on various measures of dialysis facilities.
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spelling pubmed-73183092020-06-29 The profile inter‐unit reliability He, Kevin Dahlerus, Claudia Xia, Lu Li, Yanming Kalbfleisch, John D. Biometrics Biometric Practice To assess the quality of health care, patient outcomes associated with medical providers (eg, dialysis facilities) are routinely monitored in order to identify poor (or excellent) provider performance. Given the high stakes of such evaluations for payment as well as public reporting of quality, it is important to assess the reliability of quality measures. A commonly used metric is the inter‐unit reliability (IUR), which is the proportion of variation in the measure that comes from inter‐provider differences. Despite its wide use, however, the size of the IUR has little to do with the usefulness of the measure for profiling extreme outcomes. A large IUR can signal the need for further risk adjustment to account for differences between patients treated by different providers, while even measures with an IUR close to zero can be useful for identifying extreme providers. To address these limitations, we propose an alternative measure of reliability, which assesses more directly the value of a quality measure in identifying (or profiling) providers with extreme outcomes. The resulting metric reflects the extent to which the profiling status is consistent over repeated measurements. We use national dialysis data to examine this approach on various measures of dialysis facilities. John Wiley and Sons Inc. 2019-11-10 2020-06 /pmc/articles/PMC7318309/ /pubmed/31642521 http://dx.doi.org/10.1111/biom.13167 Text en © 2019 The Authors. Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Biometric Practice
He, Kevin
Dahlerus, Claudia
Xia, Lu
Li, Yanming
Kalbfleisch, John D.
The profile inter‐unit reliability
title The profile inter‐unit reliability
title_full The profile inter‐unit reliability
title_fullStr The profile inter‐unit reliability
title_full_unstemmed The profile inter‐unit reliability
title_short The profile inter‐unit reliability
title_sort profile inter‐unit reliability
topic Biometric Practice
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318309/
https://www.ncbi.nlm.nih.gov/pubmed/31642521
http://dx.doi.org/10.1111/biom.13167
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