ArticleBMC health services research2022
Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium.
Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Development of a comprehensive real-world evidence dataset to inform diabetes policy: the diabetes data cell project.BMC public health · 2026Article
- Navigating diabetes care inequities: an observational study linking chronic care model's structural elements to process and outcomes of type 2 diabetes care in Belgium.International journal for equity in health · 2025Observational
- Implementation of an integrated care pathway for severe aortic stenosis: a prospective cohort study of clinical profiles, safety, and outcomes.Frontiers in cardiovascular medicine · 2025Article
- Scale-up of a chronic care model-based programme for type 2 diabetes in Belgium: a mixed-methods study.BMC health services research · 2023Article
- Correction: Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium.BMC health services research · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo 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.
methodsBased 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.
resultsTo 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.
conclusionIn 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.