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 and iterative 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.

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Improving the Quality of Diabetes Care in Primary Care Practice

Journal for Healthcare Quality ◽

10.1111/j.1945-1474.2004.tb00502.x ◽

2004 ◽

Vol 26 (4) ◽

pp. 14-21 ◽

Cited By ~ 14

Author(s):

Janice C. Zgibor ◽

Harsha Rao ◽

Jacqueline Wesche-Thobaben ◽

Nancie Gallagher ◽

Janis McWilliams ◽

...

Keyword(s):

Primary Care ◽

Diabetes Care ◽

Primary Care Practice ◽

Care Practice ◽

Quality Of Diabetes Care

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Cross-sectional study evaluating the association between integrated care and health-related quality of life (HRQOL) in Dutch primary care

BMJ Open ◽

10.1136/bmjopen-2020-040781 ◽

2021 ◽

Vol 11 (4) ◽

pp. e040781

Author(s):

Pim P Valentijn ◽

Marcel Kerkhoven ◽

Jantien Heideman ◽

Rosa Arends

Keyword(s):

Primary Care ◽

Integrated Care ◽

Primary Care Practice ◽

Anxiety And Depression ◽

Care Practice ◽

Cross Sectional ◽

Practice Population ◽

Related Quality ◽

Health Related

ObjectivesThe aim of this study was to evaluate the association between integrated care and health-related quality of life (HRQOL) in a primary care practice population.DesignA cross-sectional survey study.SettingPrimary care practice population.ParticipantsA sample (n=5562) of patients in two general practitioner practices in the Netherlands.Primary outcome measuresThe Rainbow Model of Integrated Care Measurement Tool patient version and EQ-5D was used to assess integrated service delivery and HRQOL. The association between integrated care and HRQOL groups was analysed using multivariate logistic regression.ResultsOverall, 933 respondents with a mean age of 62 participated (20% response rate) in this study. The multivariate analysis revealed that positive organisational coordination experiences were linked to better HRQOL (OR=1.87, 95% CI 1.18 to 2.95), and less anxiety and depression problems (OR=0.36, 95% CI 0.20 to 0.63). Unemployment was associated with a poor HRQOL (OR=0.15, 95% CI 0.08 to 0.28). Ageing was associated with more mobility (OR=1.06, 95% CI 1.04 to 1.09), self-care (OR=1.06, 95% CI 1.02 to 1.11), usual activity (OR=1.03, 95% CI 1.01 to 1.05) and pain problems (OR=1.02, 95% CI 1.01 to 1.04). Being married improved the overall HRQOL (OR=1.60, 95% CI 1.13 to 2.26) and decreased anxiety and depression (OR=0.47, 95% CI 0.31 to 0.72). Finally, females had a poor overall HRQOL (OR=1.67, 95% CI 0.48 to 0.93) and more pain and discomfort problems (OR=1.47, 95% CI 1.11 to 1.95).ConclusionThis study shows for the first time that organisational coordination activities are positively associated with HROQL of adult patients in a primary care context, adding to the evidence of an association between integrated care and HRQOL. Also, unemployment, ageing and being female are accumulating risk factors that should be considered when designing integrated primary care programmes. Further research is needed to explore how various integration types relate to HRQOL for people in local communities.

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Association Between Licensing Examination Scores and Resource Use and Quality of Care in Primary Care Practice

JAMA ◽

10.1001/jama.280.11.989 ◽

1998 ◽

Vol 280 (11) ◽

pp. 989 ◽

Cited By ~ 92

Author(s):

Robyn Tamblyn

Keyword(s):

Primary Care ◽

Quality Of Care ◽

Resource Use ◽

Primary Care Practice ◽

Care Practice ◽

Licensing Examination

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Mobile Healthcare System Provided by Primary Care Physicians Improves Quality of Diabetes Care

CardioMetabolic Syndrome Journal ◽

10.51789/cmsj.2021.1.e6 ◽

2021 ◽

Vol 1 (1) ◽

pp. 88

Author(s):

Tae Jung Oh ◽

Jie-Eun Lee ◽

Seok Kim ◽

Sooyoung Yoo ◽

Hak Chul Jang

Keyword(s):

Primary Care ◽

Healthcare System ◽

Diabetes Care ◽

Primary Care Physicians ◽

Mobile Healthcare ◽

Quality Of Diabetes Care

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A cluster randomized trial on the effect of a multifaceted intervention improved the technical quality of diabetes care by primary care physicians: The Japan Diabetes Outcome Intervention Trial‐2 (J‐ DOIT 2)

Diabetic Medicine ◽

10.1111/dme.12949 ◽

2015 ◽

Vol 33 (5) ◽

pp. 599-608 ◽

Cited By ~ 19

Author(s):

Y. Hayashino ◽

H. Suzuki ◽

K. Yamazaki ◽

A. Goto ◽

K. Izumi ◽

...

Keyword(s):

Primary Care ◽

Diabetes Care ◽

Primary Care Physicians ◽

Cluster Randomized Trial ◽

Technical Quality ◽

Intervention Trial ◽

Quality Of Diabetes Care ◽

Cluster Randomized ◽

Diabetes Outcome

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Changing diabetes® barometer: A global quality monitoring framework for improving patient outcomes

Journal of Social Health and Diabetes ◽

10.1055/s-0038-1676181 ◽

2013 ◽

Vol 01 (01) ◽

pp. 044-047

Author(s):

Pavika Jain ◽

Niels Aamand

Keyword(s):

Quality Of Care ◽

Patient Outcomes ◽

Diabetes Care ◽

Best Practice ◽

Diabetes Management ◽

Global Perspective ◽

Quality Monitoring ◽

Good Practices ◽

Quality Of Diabetes Care

This article has a global perspective and includes examples from several continents i.e. Latin America, Africa, Asia and Europe. The Changing Diabetes® Barometer (CDB) is a Novo Nordisk initiative that works as a worldwide quality monitoring system for diabetes management to measure the gains made in the fight against diabetes focusing on quality of care and patient outcomes. CDB provides a platform for countries to share local diabetes data and good practices. In doing so it aims to disseminate improved practices of care. CDB is conceptualised as a framework that can help change diabetes. Its three cornerstones are “Measure, Share, Improve” (MSI):• MEASURE the quality of diabetes care through patient outcomes and care processes.• SHARE data on the quality of diabetes care and good practices with all relevant stakeholders.• IMPROVE the quality of diabetes care by identifying and actively spreading good practices in diabetes care and inspire others to adopt and follow best practice examples.Italy and Algeria both constitute best practice examples of CDB initiatives. In Italy a registry solution is already solidly implemented and improvements in patient outcomes have been documented. The initiative in Algeria has recently been initiated including establishment of IT equipment in participating clinics to ensure all relevant measurements. This will enable transparency on current level of quality of diabetes care. Both initiatives have the common goal of driving improvements in quality of care and patient outcomes across clinics. India is another good example where data is collected through the CDB aimed at driving improvement of diabetes care in order to improve quality of life for people with diabetes. CDB in India is implemented in five states (Goa, Bihar, Gujarat, Puducherry and Andhra Pradesh) and is planned to be expanded to five additional states.

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