Filipovic-Pierucci Antoine, Samson Solène, Fagot Jean-Paul, Fagot-Campagna Anne
URC-Eco, Health economics and health policy research unit, AP-HP, Hôtel Dieu, Galerie B1-3ème étage, 1 Place du Parvis Notre Dame, Paris, 75004, France.
CNAMTS (National Health Insurance), Paris, France.
BMC Psychiatry. 2017 Jan 3;17(1):1. doi: 10.1186/s12888-016-1163-4.
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.
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.
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.
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.
为了确定心理健康方面的优先事项、制定政策以及评估公共卫生干预措施，需要定量指标。本研究的目的是通过比较不同估计方法和来源所确定的使用大量医疗资源治疗抑郁症的人群的患病率和特征，评估一个庞大且详尽的法国国家行政数据库对研究和监测抑郁症治疗情况的贡献，并讨论这些方法的优缺点。
本研究纳入了2012年主要医疗保险计划覆盖的法国人群（普通制度，占参保法国人口的86%）。数据从法国医疗保险理赔数据库（SNIIRAM）中提取，该数据库包含所有报销信息，包括法国的治疗和住院情况。SNIIRAM的以下不同来源被用于选择抑郁症患者：长期或高额疾病诊断、国家医院理赔数据以及所有国家医疗保险药品报销数据。
2012年，我们纳入了主要医疗保险计划覆盖的58,753,200人；271,275人有抑郁症的全面覆盖；179,470人曾入住精神病医院，66,595人在两年时间内入住综合医院且被诊断为抑郁症，144,670人在研究年度有超过三次抗抑郁药报销（过去5年有抑郁症住院史）。只有16%的人被不止一个来源选中。
我们提出一种算法，该算法纳入近期因抑郁症住院的人、有抑郁症住院史且仍在服用抗抑郁药的人，或作为特定长期或高额疾病有抑郁症全面覆盖的人，得出患病率估计为0.93%或544,105人。病例选择方法的变化对所选人群的频数和特征有重大影响，进而对从数据中得出的结论有重大影响，强调在研究前确定目标人群特征以产生相关结果的重要性。
