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Addressing non-response data for standardized post-acute functional items

BACKGROUND: The post-acute patient standardized functional items (Section GG) include non-response options such as refuse, not attempt and not applicable. We examined non-response patterns and compared four methods to address non-response functional data in Section GG at nation-wide inpatient rehabi...

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Autores principales: Li, Chih -Ying, Kim, Hyunkyoung, Downer, Brian, Lee, Mi Jung, Ottenbacher, Kenneth, Kuo, Yong-Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481609/
https://www.ncbi.nlm.nih.gov/pubmed/37674152
http://dx.doi.org/10.1186/s12913-023-09982-8
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author Li, Chih -Ying
Kim, Hyunkyoung
Downer, Brian
Lee, Mi Jung
Ottenbacher, Kenneth
Kuo, Yong-Fang
author_facet Li, Chih -Ying
Kim, Hyunkyoung
Downer, Brian
Lee, Mi Jung
Ottenbacher, Kenneth
Kuo, Yong-Fang
author_sort Li, Chih -Ying
collection PubMed
description BACKGROUND: The post-acute patient standardized functional items (Section GG) include non-response options such as refuse, not attempt and not applicable. We examined non-response patterns and compared four methods to address non-response functional data in Section GG at nation-wide inpatient rehabilitation facilities (IRF). METHODS: We characterized non-response patterns using 100% Medicare 2018 data. We applied four methods to generate imputed values for each non-response functional item of each patient: Monte Carlo Markov Chains multiple imputations (MCMC), Fully Conditional Specification multiple imputations (FCS), Pattern-mixture model (PMM) multiple imputations and the Centers for Medicare and Medicaid Services (CMS) approach. We compared changes of Spearman correlations and weighted kappa between Section GG and the site-specific functional items across impairments before and after applying four methods. RESULTS: One hundred fifty-nine thousand six hundred ninety-one Medicare fee-for-services beneficiaries admitted to IRFs with stroke, brain dysfunction, neurologic condition, orthopedic disorders, and debility. At discharge, 3.9% (self-care) and 61.6% (mobility) of IRF patients had at least one non-response answer in Section GG. Patients tended to have non-response data due to refused at discharge than at admission. Patients with non-response data tended to have worse function, especially in mobility; also improved less functionally compared to patients without non-response data. Overall, patients coded as ‘refused’ were more functionally independent in self-care and patients coded as ‘not applicable’ were more functionally independent in transfer and mobility, compared to other non-response answers. Four methods showed similar changes in correlations and agreements between Section GG and the site-specific functional items, but variations exist across impairments between multiple imputations and the CMS approach. CONCLUSIONS: The different reasons for non-response answers are correlated with varied functional status. The high proportion of patients with non-response data for mobility items raised a concern of biased IRF quality reporting. Our findings have potential implications for improving patient care, outcomes, quality reporting, and payment across post-acute settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-09982-8.
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spelling pubmed-104816092023-09-07 Addressing non-response data for standardized post-acute functional items Li, Chih -Ying Kim, Hyunkyoung Downer, Brian Lee, Mi Jung Ottenbacher, Kenneth Kuo, Yong-Fang BMC Health Serv Res Research BACKGROUND: The post-acute patient standardized functional items (Section GG) include non-response options such as refuse, not attempt and not applicable. We examined non-response patterns and compared four methods to address non-response functional data in Section GG at nation-wide inpatient rehabilitation facilities (IRF). METHODS: We characterized non-response patterns using 100% Medicare 2018 data. We applied four methods to generate imputed values for each non-response functional item of each patient: Monte Carlo Markov Chains multiple imputations (MCMC), Fully Conditional Specification multiple imputations (FCS), Pattern-mixture model (PMM) multiple imputations and the Centers for Medicare and Medicaid Services (CMS) approach. We compared changes of Spearman correlations and weighted kappa between Section GG and the site-specific functional items across impairments before and after applying four methods. RESULTS: One hundred fifty-nine thousand six hundred ninety-one Medicare fee-for-services beneficiaries admitted to IRFs with stroke, brain dysfunction, neurologic condition, orthopedic disorders, and debility. At discharge, 3.9% (self-care) and 61.6% (mobility) of IRF patients had at least one non-response answer in Section GG. Patients tended to have non-response data due to refused at discharge than at admission. Patients with non-response data tended to have worse function, especially in mobility; also improved less functionally compared to patients without non-response data. Overall, patients coded as ‘refused’ were more functionally independent in self-care and patients coded as ‘not applicable’ were more functionally independent in transfer and mobility, compared to other non-response answers. Four methods showed similar changes in correlations and agreements between Section GG and the site-specific functional items, but variations exist across impairments between multiple imputations and the CMS approach. CONCLUSIONS: The different reasons for non-response answers are correlated with varied functional status. The high proportion of patients with non-response data for mobility items raised a concern of biased IRF quality reporting. Our findings have potential implications for improving patient care, outcomes, quality reporting, and payment across post-acute settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-09982-8. BioMed Central 2023-09-06 /pmc/articles/PMC10481609/ /pubmed/37674152 http://dx.doi.org/10.1186/s12913-023-09982-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Li, Chih -Ying
Kim, Hyunkyoung
Downer, Brian
Lee, Mi Jung
Ottenbacher, Kenneth
Kuo, Yong-Fang
Addressing non-response data for standardized post-acute functional items
title Addressing non-response data for standardized post-acute functional items
title_full Addressing non-response data for standardized post-acute functional items
title_fullStr Addressing non-response data for standardized post-acute functional items
title_full_unstemmed Addressing non-response data for standardized post-acute functional items
title_short Addressing non-response data for standardized post-acute functional items
title_sort addressing non-response data for standardized post-acute functional items
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481609/
https://www.ncbi.nlm.nih.gov/pubmed/37674152
http://dx.doi.org/10.1186/s12913-023-09982-8
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