Literature DB >> 26897111

[Death certificate data in France: Production process and main types of analyses].

G Rey1.   

Abstract

Mortality data, by the unambiguity of their definition and understanding by all stakeholders, and completeness of registration, are a cornerstone of public health statistics in France and in most industrialized countries. This article describes the data production process, and the main types of possible analyses. Data production is composed of different stages: death certification by a medical doctor on paper or electronic (using a web application) format, data transmission to Inserm, capture and coding of information. The encoding of the information follows the WHO recommendations of the International Classification of Diseases ([ICD], 10th revision used since 2000). It is carried out using an automatic coding software, called Iris, developed in an international consortium. The coding aims, first, at assigning an ICD code to all nosologic entities encountered on the certificate, and then at selecting the underlying cause of death. The latter is the main information used for statistical analyses. Three main types of analysis emerge in the literature: the exploitation of data on the death certificate only, ecological analyses (studies of associations between variables measured across groups) and analysis from data individually linked to other databases. Many public health issues can be addressed with these various analyses. Several developments in the production process are being implemented: the deployment of electronic certification, increased automation of the death certificate information processing and durable and complete record linkage with health insurance and hospitalisation data. They could soon be deeply expanding the scope of possible uses of causes of death data.
Copyright © 2016 Société Nationale Française de Médecine Interne (SNFMI). Published by Elsevier SAS. All rights reserved.

Entities:  

Keywords:  Causes de décès; Causes of death; Codage médical; Medical coding; National statistics; Public health; Santé publique; Statistique nationale

Mesh:

Year:  2016        PMID: 26897111     DOI: 10.1016/j.revmed.2016.01.011

Source DB:  PubMed          Journal:  Rev Med Interne        ISSN: 0248-8663            Impact factor:   0.728


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