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01-04-2019 | Original Article

Identifying diabetes cases in health administrative databases: a validation study based on a large French cohort

Authors: Sonsoles Fuentes, Emmanuel Cosson, Laurence Mandereau-Bruno, Anne Fagot-Campagna, Pascale Bernillon, Marcel Goldberg, Sandrine Fosse-Edorh, CONSTANCES-Diab Group

Published in: International Journal of Public Health | Issue 3/2019

Abstract

Objectives

In the French national health insurance information system (SNDS) three diabetes case definition algorithms are applied to identify diabetic patients. The objective of this study was to validate those using data from a large cohort.

Methods

The CONSTANCES cohort (Cohorte des consultants des Centres d’examens de santé) comprises a randomly selected sample of adults living in France. Between 2012 and 2014, data from 45,739 participants recorded in a self-administrated questionnaire and in a medical examination were linked to the SNDS. Two gold standards were defined: known diabetes and pharmacologically treated diabetes. Sensitivity, specificity, positive and negative predictive values (PPV, NPV) and kappa coefficients (k) were estimated.

Results

All three algorithms had specificities and NPV over 99%. Their sensitivities ranged from 73 to 77% in algorithm A, to 86 and 97% in algorithm B and to 93 and 99% in algorithm C, when identifying known and pharmacologically treated diabetes, respectively. Algorithm C had the highest k when using known diabetes as the gold standard (0.95). Algorithm B had the highest k (0.98) when testing for pharmacologically treated diabetes.

Conclusions

The SNDS is an excellent source for diabetes surveillance and studies on diabetes since the case definition algorithms applied have very good test performances.

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Title: Identifying diabetes cases in health administrative databases: a validation study based on a large French cohort
Authors: Sonsoles Fuentes
Emmanuel Cosson
Laurence Mandereau-Bruno
Anne Fagot-Campagna
Pascale Bernillon
Marcel Goldberg
Sandrine Fosse-Edorh
CONSTANCES-Diab Group
Publication date: 01-04-2019
Publisher: Springer International Publishing
Published in: International Journal of Public Health / Issue 3/2019
Print ISSN: 1661-8556
Electronic ISSN: 1661-8564
DOI: https://doi.org/10.1007/s00038-018-1186-3

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Identifying diabetes cases in health administrative databases: a validation study based on a large French cohort

Abstract

Objectives

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Objectives

Methods

Results

Conclusions

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