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A cross-sectoral approach to utilizing health claims data for quality assurance in medical rehabilitation: study protocol of a combined prospective longitudinal and retrospective cohort study
BACKGROUND: Measuring the quality of provided healthcare presents many challenges, especially in the context of medical rehabilitation. Rehabilitation is based on a holistic biopsychosocial model of health that includes a person’s long-term functioning; hence, outcome domains are very diverse. In Ge...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583441/ https://www.ncbi.nlm.nih.gov/pubmed/37848889 http://dx.doi.org/10.1186/s12913-023-10074-w |
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author | Kaiser, Vanessa Fichtner, Urs A. Schmuker, Caroline Günster, Christian Rau, Diana Staab, Lena Farin-Glattacker, Erik |
author_facet | Kaiser, Vanessa Fichtner, Urs A. Schmuker, Caroline Günster, Christian Rau, Diana Staab, Lena Farin-Glattacker, Erik |
author_sort | Kaiser, Vanessa |
collection | PubMed |
description | BACKGROUND: Measuring the quality of provided healthcare presents many challenges, especially in the context of medical rehabilitation. Rehabilitation is based on a holistic biopsychosocial model of health that includes a person’s long-term functioning; hence, outcome domains are very diverse. In Germany, rehabilitation outcomes are currently assessed via patient and physician surveys. Health insurance claims data has the potential to simplify current quality assurance procedures in Germany, since its comprehensive collection is federally mandated from every healthcare provider. By using a cross-sectoral approach, quality assessments in rehabilitation can be adjusted for the quality provided in previous sectors and individual patient risk factors. METHODS: SEQUAR combines two studies: In a prospective longitudinal study, 600 orthopedic rehabilitation patients and their physicians are surveyed at 4 and 2 time points, respectively, throughout rehabilitation and a follow-up period of 6 months. The questionnaires include validated instruments used in the current best-practice quality assurance procedures. In a retrospective cohort study, a nationwide claims database with more than 312,000 orthopedic rehabilitation patients will be used to perform exploratory analysis for the identification of quality indicators. The identified SEQUAR claims data quality indicators will be calculated for our prospective study participants and tested for their ability to approximate or replace the currently used, best-practice quality indicators based on primary data. DISCUSSION: The identified SEQUAR quality indicators will be used to draft a novel, state-of-the-art quality assurance procedure that reduces the administrative burden of current procedures. Further research into the applicability to other indications of rehabilitation is required. TRIAL REGISTRATION: WHO UTN: U1111-1276-7141; DRKS-ID: DRKS00028747 (Date of Registration in DRKS: 2022/08/10). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-10074-w. |
format | Online Article Text |
id | pubmed-10583441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105834412023-10-19 A cross-sectoral approach to utilizing health claims data for quality assurance in medical rehabilitation: study protocol of a combined prospective longitudinal and retrospective cohort study Kaiser, Vanessa Fichtner, Urs A. Schmuker, Caroline Günster, Christian Rau, Diana Staab, Lena Farin-Glattacker, Erik BMC Health Serv Res Study Protocol BACKGROUND: Measuring the quality of provided healthcare presents many challenges, especially in the context of medical rehabilitation. Rehabilitation is based on a holistic biopsychosocial model of health that includes a person’s long-term functioning; hence, outcome domains are very diverse. In Germany, rehabilitation outcomes are currently assessed via patient and physician surveys. Health insurance claims data has the potential to simplify current quality assurance procedures in Germany, since its comprehensive collection is federally mandated from every healthcare provider. By using a cross-sectoral approach, quality assessments in rehabilitation can be adjusted for the quality provided in previous sectors and individual patient risk factors. METHODS: SEQUAR combines two studies: In a prospective longitudinal study, 600 orthopedic rehabilitation patients and their physicians are surveyed at 4 and 2 time points, respectively, throughout rehabilitation and a follow-up period of 6 months. The questionnaires include validated instruments used in the current best-practice quality assurance procedures. In a retrospective cohort study, a nationwide claims database with more than 312,000 orthopedic rehabilitation patients will be used to perform exploratory analysis for the identification of quality indicators. The identified SEQUAR claims data quality indicators will be calculated for our prospective study participants and tested for their ability to approximate or replace the currently used, best-practice quality indicators based on primary data. DISCUSSION: The identified SEQUAR quality indicators will be used to draft a novel, state-of-the-art quality assurance procedure that reduces the administrative burden of current procedures. Further research into the applicability to other indications of rehabilitation is required. TRIAL REGISTRATION: WHO UTN: U1111-1276-7141; DRKS-ID: DRKS00028747 (Date of Registration in DRKS: 2022/08/10). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-10074-w. BioMed Central 2023-10-17 /pmc/articles/PMC10583441/ /pubmed/37848889 http://dx.doi.org/10.1186/s12913-023-10074-w 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 | Study Protocol Kaiser, Vanessa Fichtner, Urs A. Schmuker, Caroline Günster, Christian Rau, Diana Staab, Lena Farin-Glattacker, Erik A cross-sectoral approach to utilizing health claims data for quality assurance in medical rehabilitation: study protocol of a combined prospective longitudinal and retrospective cohort study |
title | A cross-sectoral approach to utilizing health claims data for quality assurance in medical rehabilitation: study protocol of a combined prospective longitudinal and retrospective cohort study |
title_full | A cross-sectoral approach to utilizing health claims data for quality assurance in medical rehabilitation: study protocol of a combined prospective longitudinal and retrospective cohort study |
title_fullStr | A cross-sectoral approach to utilizing health claims data for quality assurance in medical rehabilitation: study protocol of a combined prospective longitudinal and retrospective cohort study |
title_full_unstemmed | A cross-sectoral approach to utilizing health claims data for quality assurance in medical rehabilitation: study protocol of a combined prospective longitudinal and retrospective cohort study |
title_short | A cross-sectoral approach to utilizing health claims data for quality assurance in medical rehabilitation: study protocol of a combined prospective longitudinal and retrospective cohort study |
title_sort | cross-sectoral approach to utilizing health claims data for quality assurance in medical rehabilitation: study protocol of a combined prospective longitudinal and retrospective cohort study |
topic | Study Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583441/ https://www.ncbi.nlm.nih.gov/pubmed/37848889 http://dx.doi.org/10.1186/s12913-023-10074-w |
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