Delon François, Mayet Aurélie, Thellier Marc, Kendjo Eric, Michel Rémy, Ollivier Lénaïck, Chatellier Gilles, Desjeux Guillaume
French Armed Forces Center for Epidemiology and Public Health, Marseille, France.
UMR 912: INSERM-IRD-Aix-Marseille University, Marseille, France.
J Am Med Inform Assoc. 2017 May 1;24(3):588-595. doi: 10.1093/jamia/ocw164.
Epidemiological surveillance of malaria in France is based on a hospital laboratory sentinel surveillance network. There is no comprehensive population surveillance. The objective of this study was to assess the ability of the French National Health Insurance Information System to support nationwide malaria surveillance in continental France.
A case identification algorithm was built in a 2-step process. First, inclusion rules giving priority to sensitivity were defined. Then, based on data description, exclusion rules to increase specificity were applied. To validate our results, we compared them to data from the French National Reference Center for Malaria on case counts, distribution within subgroups, and disease onset date trends.
We built a reusable automatized tool. From July 1, 2013, to June 30, 2014, we identified 4077 incident malaria cases that occurred in continental France. Our algorithm provided data for hospitalized patients, patients treated by private physicians, and outpatients for the entire population. Our results were similar to those of the National Reference Center for Malaria for each of the outcome criteria.
We provided a reliable algorithm for implementing epidemiological surveillance of malaria based on the French National Health Insurance Information System. Our method allowed us to work on the entire population living in continental France, including subpopulations poorly covered by existing surveillance methods.
Traditional epidemiological surveillance and the approach presented in this paper are complementary, but a formal validation framework for case identification algorithms is necessary.
法国疟疾的流行病学监测基于医院实验室哨点监测网络。目前尚无全面的人群监测。本研究的目的是评估法国国家健康保险信息系统支持法国大陆地区全国疟疾监测的能力。
通过两步流程构建病例识别算法。首先，定义优先考虑敏感性的纳入规则。然后，根据数据描述，应用提高特异性的排除规则。为验证我们的结果，我们将其与法国国家疟疾参考中心在病例数、亚组内分布以及发病日期趋势方面的数据进行了比较。
我们构建了一个可重复使用的自动化工具。在2013年7月1日至2014年6月30日期间，我们识别出在法国大陆发生的4077例新发疟疾病例。我们的算法为住院患者、私人医生治疗的患者以及全体人群的门诊患者提供了数据。我们的结果在每个结果标准方面都与国家疟疾参考中心的结果相似。
我们基于法国国家健康保险信息系统提供了一种实施疟疾流行病学监测的可靠算法。我们的方法使我们能够对居住在法国大陆的全体人群开展工作，包括现有监测方法覆盖不足的亚人群。
传统的流行病学监测与本文提出的方法是互补的，但病例识别算法需要一个正式的验证框架。
