ArticleJournal of the American Medical Informatics Association : JAMIA2017
Assessment of the French National Health Insurance Information System as a tool for epidemiological surveillance of malaria.
Article in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Predicting the risk of malaria re-introduction in countries certified malaria-free: a systematic review.Malaria journal · 2023Pooled it
- Asymptomatic and submicroscopic Plasmodium vivax infection: a study previous to malaria-free certification in Argentina.Malaria journal · 2026Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveEpidemiological 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. MATERIALS AND
methodsA 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.
resultsWe 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. DISCUSSION: 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.
conclusionTraditional epidemiological surveillance and the approach presented in this paper are complementary, but a formal validation framework for case identification algorithms is necessary.
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