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Review
. 2021 Oct 11:2:744516.
doi: 10.3389/fcdhc.2021.744516. eCollection 2021.

Making Use of Comparable Health Data to Improve Quality of Care and Outcomes in Diabetes: The EUBIROD Review of Diabetes Registries and Data Sources in Europe

Fabrizio Carinci  1 , Iztok Štotl  2   3 , Scott G Cunningham  4 , Tamara Poljicanin  5 , Ivan Pristas  5 , Vivie Traynor  6 , George Olympios  6 , Vasos Scoutellas  6   7 , Joseph Azzopardi  8 , Kris Doggen  9 , János Sandor  10 , Roza Adany  10 , Karianne F Løvaas  11 , Przemka Jarosz-Chobot  12 , Joanna Polanska  13 , Simion Pruna  14 , Simon de Lusignan  15 , Marcello Monesi  16   17 , Paolo Di Bartolo  17   18 , Christa Scheidt-Nave  19 , Christin Heidemann  19 , Inbar Zucker  20   21 , Anita Maurina  22 , Jana Lepiksone  22 , Peter Rossing  23 , Martti Arffman  24 , Ilmo Keskimäki  24   25 , Soffia Gudbjornsdottir  26 , Concetta Tania Di Iorio  27 , Elisabeth Dupont  28 , Stella de Sabata  28 , Niek Klazinga  29 , Massimo Massi Benedetti  28   30
Affiliations
Review

Making Use of Comparable Health Data to Improve Quality of Care and Outcomes in Diabetes: The EUBIROD Review of Diabetes Registries and Data Sources in Europe

Fabrizio Carinci et al. Front Clin Diabetes Healthc. .

Abstract

Background: Registries and data sources contain information that can be used on an ongoing basis to improve quality of care and outcomes of people with diabetes. As a specific task of the EU Bridge Health project, we carried out a survey of diabetes-related data sources in Europe.

Objectives: We aimed to report on the organization of different sources of diabetes information, including their governance, information infrastructure and dissemination strategies for quality control, service planning, public health, policy and research.

Methods: Survey using a structured questionnaire to collect targeted data from a network of collaborating institutions managing registries and data sources in 17 countries in the year 2017.

Results: The 18 data sources participating in the study were most frequently academic centres (44.4%), national (72.2%), targeting all types of diabetes (61.1%) covering no more than 10% of the target population (44.4%). Although population-based in over a quarter of cases (27.8%), sources relied predominantly on provider-based datasets (38.5%), fewer using administrative data (16.6%). Data collection was continuous in the majority of cases (61.1%), but 50% could not perform data linkage. Public reports were more frequent (72.2%) as well as quality reports (77.8%), but one third did not provide feedback to policy and only half published ten or more peer reviewed papers during the last 5 years.

Conclusions: The heterogeneous implementation of diabetes registries and data sources hampers the comparability of quality and outcomes across Europe. Best practices exist but need to be shared more effectively to accelerate progress and deliver equitable results for people with diabetes.

Keywords: diabetes; diabetes registries; health information; performance indicators; quality of care; risk adjustment.

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Conflict of interest statement

SL is the Director of the RCGP RSC, as part of his academic work. He has received grants through his institution from AstraZeneca, Eli Lilly, Novo, and Sanofi, for diabetes related research. SC is employed by My Digital Health. CI is employed by Serectrix snc. SP was employed by Telemedica Consulting. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
General characteristics of diabetes registries and data sources included in the survey (N=18).
Figure 2
Figure 2
Data characteristics of diabetes registries and data sources included in the survey (N=18).
Figure 3
Figure 3
Outputs of diabetes registries and data sources included in the survey (N=18).
Figure 4
Figure 4
Reliability of indicators derived from different data schemes. At left: different combinations of data sets. At right: the resulting indicator, presented for convenience as the typical quality of care indicator, including the number of cases with negative outcomes in the numerator (e.g. the number of subjects with major amputations) and the reference population in the denominator (e.g. the number of people with diabetes).
See this image and copyright information in PMC

References

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