Cargando…
Estimating the prevalence of depression associated with healthcare use in France using administrative databases
BACKGROUND: Quantitative indicators are needed in order to define priorities, plan policies and evaluate public health interventions in mental health. The aim of this study was to assess the contribution of a large and exhaustive French national administrative database to study and monitor treated d...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5209826/ https://www.ncbi.nlm.nih.gov/pubmed/28049496 http://dx.doi.org/10.1186/s12888-016-1163-4 |
_version_ | 1782490800617160704 |
---|---|
author | Filipovic-Pierucci, Antoine Samson, Solène Fagot, Jean-Paul Fagot-Campagna, Anne |
author_facet | Filipovic-Pierucci, Antoine Samson, Solène Fagot, Jean-Paul Fagot-Campagna, Anne |
author_sort | Filipovic-Pierucci, Antoine |
collection | PubMed |
description | BACKGROUND: Quantitative indicators are needed in order to define priorities, plan policies and evaluate public health interventions in mental health. The aim of this study was to assess the contribution of a large and exhaustive French national administrative database to study and monitor treated depression by comparing the prevalence and characteristics of the population using significant healthcare resources for depression as identified by different estimation methods and sources and to discuss the advantages and drawbacks of these methods. METHODS: This study included the French population covered by the main health insurance scheme in 2012 (Régime général, 86% of the insured French population). Data were extracted from the French health insurance claim database (SNIIRAM), which contains information on all reimbursements, including treatments and hospital stays in France. The following distinct sources of the SNIIRAM were used to select persons with depression: diagnoses of long-term or costly conditions, data from national hospital claims and data concerning all national health insurance reimbursements for drugs. RESULTS: In 2012, we included 58,753,200 individuals covered by the main health insurance scheme; 271,275 individuals had full coverage for depression; 179,470 individuals had been admitted to a psychiatric hospital and 66,595 individuals admitted to a general hospital with a diagnosis of depression during a 2-year timeframe and 144,670 individuals had more than three reimbursements for antidepressants during the study year (with a history of hospitalisation for depression during the past 5 years). Only 16% of individuals were selected by more than one source. CONCLUSIONS: We propose an algorithm that includes persons recently hospitalised for depression, or with a history of hospitalisation for depression and still taking antidepressants, or with full coverage for depression as a specific long-term or costly condition, yielding a prevalence estimate of 0.93% or 544,105 individuals. Changes in the case selection methodology have major consequences on the frequency count and characteristics of the selected population, and consequently on the conclusions that can be drawn from the data, emphasizing the importance of defining the characteristics of the target population before the study in order to produce relevant results. |
format | Online Article Text |
id | pubmed-5209826 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-52098262017-01-04 Estimating the prevalence of depression associated with healthcare use in France using administrative databases Filipovic-Pierucci, Antoine Samson, Solène Fagot, Jean-Paul Fagot-Campagna, Anne BMC Psychiatry Research Article BACKGROUND: Quantitative indicators are needed in order to define priorities, plan policies and evaluate public health interventions in mental health. The aim of this study was to assess the contribution of a large and exhaustive French national administrative database to study and monitor treated depression by comparing the prevalence and characteristics of the population using significant healthcare resources for depression as identified by different estimation methods and sources and to discuss the advantages and drawbacks of these methods. METHODS: This study included the French population covered by the main health insurance scheme in 2012 (Régime général, 86% of the insured French population). Data were extracted from the French health insurance claim database (SNIIRAM), which contains information on all reimbursements, including treatments and hospital stays in France. The following distinct sources of the SNIIRAM were used to select persons with depression: diagnoses of long-term or costly conditions, data from national hospital claims and data concerning all national health insurance reimbursements for drugs. RESULTS: In 2012, we included 58,753,200 individuals covered by the main health insurance scheme; 271,275 individuals had full coverage for depression; 179,470 individuals had been admitted to a psychiatric hospital and 66,595 individuals admitted to a general hospital with a diagnosis of depression during a 2-year timeframe and 144,670 individuals had more than three reimbursements for antidepressants during the study year (with a history of hospitalisation for depression during the past 5 years). Only 16% of individuals were selected by more than one source. CONCLUSIONS: We propose an algorithm that includes persons recently hospitalised for depression, or with a history of hospitalisation for depression and still taking antidepressants, or with full coverage for depression as a specific long-term or costly condition, yielding a prevalence estimate of 0.93% or 544,105 individuals. Changes in the case selection methodology have major consequences on the frequency count and characteristics of the selected population, and consequently on the conclusions that can be drawn from the data, emphasizing the importance of defining the characteristics of the target population before the study in order to produce relevant results. BioMed Central 2017-01-03 /pmc/articles/PMC5209826/ /pubmed/28049496 http://dx.doi.org/10.1186/s12888-016-1163-4 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Filipovic-Pierucci, Antoine Samson, Solène Fagot, Jean-Paul Fagot-Campagna, Anne Estimating the prevalence of depression associated with healthcare use in France using administrative databases |
title | Estimating the prevalence of depression associated with healthcare use in France using administrative databases |
title_full | Estimating the prevalence of depression associated with healthcare use in France using administrative databases |
title_fullStr | Estimating the prevalence of depression associated with healthcare use in France using administrative databases |
title_full_unstemmed | Estimating the prevalence of depression associated with healthcare use in France using administrative databases |
title_short | Estimating the prevalence of depression associated with healthcare use in France using administrative databases |
title_sort | estimating the prevalence of depression associated with healthcare use in france using administrative databases |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5209826/ https://www.ncbi.nlm.nih.gov/pubmed/28049496 http://dx.doi.org/10.1186/s12888-016-1163-4 |
work_keys_str_mv | AT filipovicpierucciantoine estimatingtheprevalenceofdepressionassociatedwithhealthcareuseinfranceusingadministrativedatabases AT samsonsolene estimatingtheprevalenceofdepressionassociatedwithhealthcareuseinfranceusingadministrativedatabases AT fagotjeanpaul estimatingtheprevalenceofdepressionassociatedwithhealthcareuseinfranceusingadministrativedatabases AT fagotcampagnaanne estimatingtheprevalenceofdepressionassociatedwithhealthcareuseinfranceusingadministrativedatabases |