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

Abstract

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.

Scale-up of a chronic care model-based programme for type 2 diabetes in Belgium: a mixed-methods study

“…Another alternative explanation is that providers in the capitation system have more experience with diabetes and therefore score higher. This is probable, as the preliminary analysis from our follow-up study [57], indicates that capitation practices have a prevalence of 12% of patients with diabetes, compared to 8% in the other practices. On the other hand, practitioners in fee-for-service practices also complained that their financing system withholds them from delegating more tasks, as the more tasks are delegated, the less they earn.…”

What is meant by ‘integrated personalized diabetes management’: A view into the future and what success should look like

“…72,73 It should facilitate quality monitoring across the care continuum that is, data related to system, process and outcome indicators. 74 Data are an important part of understanding the impact of diabetes and evaluating diabetes programmes and their outcomes. Many national health systems, even those in developed countries, lack a sufficient data exchange system to support integrated care management across different organizations.…”

“…A data exchange infrastructure for integrated diabetes care should make communication seamless between all users across organizations and among different information technology systems, devices, and software applications such as electronic health records (EHRs) 72,73 . It should facilitate quality monitoring across the care continuum that is, data related to system, process and outcome indicators 74 . Data are an important part of understanding the impact of diabetes and evaluating diabetes programmes and their outcomes.…”

“…One should be able to monitor the patient throughout the care process and measure the related health outcomes, while also collecting data on the overall IPDM network performance, resource utilization and healthcare infrastructure characteristics. Various useful assessment frameworks for IPDM have been proposed and applied 24,74,142,147 …”

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

“…Following publication of the original article [ 1 ], the authors identified an error in the author names. The given names and family names of all authors (except for one) were erroneously transposed.…”