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Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium

BACKGROUND: To assess the quality of integrated diabetes care, we should be able to follow the patient throughout the care path, monitor his/her care process and link them to his/her health outcomes, while simultaneously link this information to the primary care system and its performance on the str...

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Autores principales: Veerle, Buffel, Katrien, Danhieux, Bos, Philippe, Roy, Remmen, Josefien, Van Olmen, Edwin, Wouters
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9578257/
https://www.ncbi.nlm.nih.gov/pubmed/36253775
http://dx.doi.org/10.1186/s12913-022-08625-8
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author Veerle, Buffel
Katrien, Danhieux
Bos, Philippe
Roy, Remmen
Josefien, Van Olmen
Edwin, Wouters
author_facet Veerle, Buffel
Katrien, Danhieux
Bos, Philippe
Roy, Remmen
Josefien, Van Olmen
Edwin, Wouters
author_sort Veerle, Buffel
collection PubMed
description BACKGROUND: To assess the quality of integrated diabetes care, we should be able to follow the patient throughout the care path, monitor his/her care process and link them to his/her health outcomes, while simultaneously link this information to the primary care system and its performance on the structure and organization related quality indicators. However the development process of such a data framework is challenging, even in period of increasing and improving health data storage and management. This study aims to develop an integrated multi-level data framework for quality of diabetes care and to operationalize this framework in the fragmented Belgium health care and data landscape. METHODS: Based on document reviews, iterative working group discussions and expert consultations, theoretical approaches and quality indicators were identified and assessed. After mapping and assessing the validity of existing health information systems and available data sources through expert consultations, the theoretical framework was translated in a data framework with measurable quality indicators. The construction of the data base included sampling procedures, data-collection, and several technical and privacy-related aspects of linking and accessing Belgian datasets. RESULTS: To address three dimensions of quality of care, we integrated the chronic care model and cascade of care approach, addressing respectively the structure related quality indicators and the process and outcome related indicators. The corresponding data framework is based on self-collected data at the primary care practice level (using the Assessment of quality of integrated care tool), and linked health insurance data with lab data at the patient level. CONCLUSION: In this study, we have described the transition of a theoretical quality of care framework to a unique multilevel database, which allows assessing the quality of diabetes care, by considering the complete care continuum (process and outcomes) as well as organizational characteristics of primary care practices. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08625-8.
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spelling pubmed-95782572022-10-19 Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium Veerle, Buffel Katrien, Danhieux Bos, Philippe Roy, Remmen Josefien, Van Olmen Edwin, Wouters BMC Health Serv Res Research BACKGROUND: To assess the quality of integrated diabetes care, we should be able to follow the patient throughout the care path, monitor his/her care process and link them to his/her health outcomes, while simultaneously link this information to the primary care system and its performance on the structure and organization related quality indicators. However the development process of such a data framework is challenging, even in period of increasing and improving health data storage and management. This study aims to develop an integrated multi-level data framework for quality of diabetes care and to operationalize this framework in the fragmented Belgium health care and data landscape. METHODS: Based on document reviews, iterative working group discussions and expert consultations, theoretical approaches and quality indicators were identified and assessed. After mapping and assessing the validity of existing health information systems and available data sources through expert consultations, the theoretical framework was translated in a data framework with measurable quality indicators. The construction of the data base included sampling procedures, data-collection, and several technical and privacy-related aspects of linking and accessing Belgian datasets. RESULTS: To address three dimensions of quality of care, we integrated the chronic care model and cascade of care approach, addressing respectively the structure related quality indicators and the process and outcome related indicators. The corresponding data framework is based on self-collected data at the primary care practice level (using the Assessment of quality of integrated care tool), and linked health insurance data with lab data at the patient level. CONCLUSION: In this study, we have described the transition of a theoretical quality of care framework to a unique multilevel database, which allows assessing the quality of diabetes care, by considering the complete care continuum (process and outcomes) as well as organizational characteristics of primary care practices. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08625-8. BioMed Central 2022-10-18 /pmc/articles/PMC9578257/ /pubmed/36253775 http://dx.doi.org/10.1186/s12913-022-08625-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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
Veerle, Buffel
Katrien, Danhieux
Bos, Philippe
Roy, Remmen
Josefien, Van Olmen
Edwin, Wouters
Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium
title Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium
title_full Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium
title_fullStr Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium
title_full_unstemmed Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium
title_short Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium
title_sort development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of belgium
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9578257/
https://www.ncbi.nlm.nih.gov/pubmed/36253775
http://dx.doi.org/10.1186/s12913-022-08625-8
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