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Rev Epidemiol Sante Publique. 2017 Oct;65 Suppl 4:S168-S173. doi: 10.1016/j.respe.2017.05.001. Epub 2017 Jul 29.

[Algorithms based on medico-administrative data in the field of endocrine, nutritional and metabolic diseases, especially diabetes].

[Article in French]

Author information

1
Santé publique France, 12, rue du Val-d'Osne, 94415 Saint-Maurice cedex, France. Electronic address: sandrine.fosse@santepubliquefrance.fr.
2
Santé publique France, 12, rue du Val-d'Osne, 94415 Saint-Maurice cedex, France.
3
Haute Autorité de santé, 93210 Saint-Denis, France.
4
Inserm (U1153), Inra (U1125), université Paris 13, équipe de recherche en épidémiologie nutritionnelle (EREN), centre de recherche en épidémiologie et statistiques, Cnam, COMUE, Sorbonne Paris Cité, 93000 Bobigny, France.
5
Caisse nationale d'assurance maladie des travailleurs salariés, 75020 Paris, France.

Abstract

BACKGROUND:

Medico-administrative databases represent a very interesting source of information in the field of endocrine, nutritional and metabolic diseases. The objective of this article is to describe the early works of the Redsiam working group in this field.

METHODS:

Algorithms developed in France in the field of diabetes, the treatment of dyslipidemia, precocious puberty, and bariatric surgery based on the National Inter-schema Information System on Health Insurance (SNIIRAM) data were identified and described.

RESULTS:

Three algorithms for identifying people with diabetes are available in France. These algorithms are based either on full insurance coverage for diabetes or on claims of diabetes treatments, or on the combination of these two methods associated with hospitalizations related to diabetes. Each of these algorithms has a different purpose, and the choice should depend on the goal of the study. Algorithms for identifying people treated for dyslipidemia or precocious puberty or who underwent bariatric surgery are also available.

CONCLUSION:

Early work from the Redsiam working group in the field of endocrine, nutritional and metabolic diseases produced an inventory of existing algorithms in France, linked with their goals, together with a presentation of their limitations and advantages, providing useful information for the scientific community. This work will continue with discussions about algorithms on the incidence of diabetes in children, thyroidectomy for thyroid nodules, hypothyroidism, hypoparathyroidism, and amyloidosis.

KEYWORDS:

Algorithm; Algorithme; Bariatric surgery; Chirurgie bariatrique; Diabetes; Diabète; Dyslipidemia; Dyslipidémie; Precocious puberty; Puberté précoce

PMID:
28625707
DOI:
10.1016/j.respe.2017.05.001
[Indexed for MEDLINE]

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