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Assessing the effect of a regional integrated care model over ten years using quality indicators based on claims data – the basic statistical methodology of the INTEGRAL project
BACKGROUND: The regional integrated health care model “Healthy Kinzigtal” started in 2006 with the goal of optimizing health care and economic efficiency. The INTEGRAL project aimed at evaluating the effect of this model on the quality of care over the first 10 years. METHODS: This methodological pr...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8867633/ https://www.ncbi.nlm.nih.gov/pubmed/35197048 http://dx.doi.org/10.1186/s12913-022-07573-7 |
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author | Stelzer, Dominikus Graf, Erika Köster, Ingrid Ihle, Peter Günster, Christian Dröge, Patrik Klöss, Andreas Mehl, Claudia Farin-Glattacker, Erik Geraedts, Max Schubert, Ingrid Siegel, Achim Vach, Werner |
author_facet | Stelzer, Dominikus Graf, Erika Köster, Ingrid Ihle, Peter Günster, Christian Dröge, Patrik Klöss, Andreas Mehl, Claudia Farin-Glattacker, Erik Geraedts, Max Schubert, Ingrid Siegel, Achim Vach, Werner |
author_sort | Stelzer, Dominikus |
collection | PubMed |
description | BACKGROUND: The regional integrated health care model “Healthy Kinzigtal” started in 2006 with the goal of optimizing health care and economic efficiency. The INTEGRAL project aimed at evaluating the effect of this model on the quality of care over the first 10 years. METHODS: This methodological protocol supplements the study protocol and the main publication of the project. Comparing quality indicators based on claims data between the intervention region and 13 structurally similar control regions constitutes the basic scientific approach. Methodological key issues in performing such a comparison are identified and solutions are presented. RESULTS: A key step in the analysis is the assessment of a potential trend in prevalence for a single quality indicator over time in the intervention region compared to the corresponding trends in the control regions. This step has to take into account that there may be a common - not necessarily linear - trend in the indicator over time and that trends can also appear by chance. Conceptual and statistical approaches were developed to handle this key step and to assess in addition the overall evidence for an intervention effect across all indicators. The methodology can be extended in several directions of interest. CONCLUSIONS: We believe that our approach can handle the major statistical challenges: population differences are addressed by standardization; we offer transparency with respect to the derivation of the key figures; global time trends and structural changes do not invalidate the analyses; the regional variation in time trends is taken into account. Overall, the project demanded substantial efforts to ensure adequateness, validity and transparency. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12913-022-07573-7). |
format | Online Article Text |
id | pubmed-8867633 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88676332022-02-28 Assessing the effect of a regional integrated care model over ten years using quality indicators based on claims data – the basic statistical methodology of the INTEGRAL project Stelzer, Dominikus Graf, Erika Köster, Ingrid Ihle, Peter Günster, Christian Dröge, Patrik Klöss, Andreas Mehl, Claudia Farin-Glattacker, Erik Geraedts, Max Schubert, Ingrid Siegel, Achim Vach, Werner BMC Health Serv Res Research Article BACKGROUND: The regional integrated health care model “Healthy Kinzigtal” started in 2006 with the goal of optimizing health care and economic efficiency. The INTEGRAL project aimed at evaluating the effect of this model on the quality of care over the first 10 years. METHODS: This methodological protocol supplements the study protocol and the main publication of the project. Comparing quality indicators based on claims data between the intervention region and 13 structurally similar control regions constitutes the basic scientific approach. Methodological key issues in performing such a comparison are identified and solutions are presented. RESULTS: A key step in the analysis is the assessment of a potential trend in prevalence for a single quality indicator over time in the intervention region compared to the corresponding trends in the control regions. This step has to take into account that there may be a common - not necessarily linear - trend in the indicator over time and that trends can also appear by chance. Conceptual and statistical approaches were developed to handle this key step and to assess in addition the overall evidence for an intervention effect across all indicators. The methodology can be extended in several directions of interest. CONCLUSIONS: We believe that our approach can handle the major statistical challenges: population differences are addressed by standardization; we offer transparency with respect to the derivation of the key figures; global time trends and structural changes do not invalidate the analyses; the regional variation in time trends is taken into account. Overall, the project demanded substantial efforts to ensure adequateness, validity and transparency. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12913-022-07573-7). BioMed Central 2022-02-24 /pmc/articles/PMC8867633/ /pubmed/35197048 http://dx.doi.org/10.1186/s12913-022-07573-7 Text en © The Author(s) 2022, , corrected publication 2022 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 Article Stelzer, Dominikus Graf, Erika Köster, Ingrid Ihle, Peter Günster, Christian Dröge, Patrik Klöss, Andreas Mehl, Claudia Farin-Glattacker, Erik Geraedts, Max Schubert, Ingrid Siegel, Achim Vach, Werner Assessing the effect of a regional integrated care model over ten years using quality indicators based on claims data – the basic statistical methodology of the INTEGRAL project |
title | Assessing the effect of a regional integrated care model over ten years using quality indicators based on claims data – the basic statistical methodology of the INTEGRAL project |
title_full | Assessing the effect of a regional integrated care model over ten years using quality indicators based on claims data – the basic statistical methodology of the INTEGRAL project |
title_fullStr | Assessing the effect of a regional integrated care model over ten years using quality indicators based on claims data – the basic statistical methodology of the INTEGRAL project |
title_full_unstemmed | Assessing the effect of a regional integrated care model over ten years using quality indicators based on claims data – the basic statistical methodology of the INTEGRAL project |
title_short | Assessing the effect of a regional integrated care model over ten years using quality indicators based on claims data – the basic statistical methodology of the INTEGRAL project |
title_sort | assessing the effect of a regional integrated care model over ten years using quality indicators based on claims data – the basic statistical methodology of the integral project |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8867633/ https://www.ncbi.nlm.nih.gov/pubmed/35197048 http://dx.doi.org/10.1186/s12913-022-07573-7 |
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