Improving disease incidence estimates in primary care surveillance systems

Population Health Metrics

Pierre-Yves Boëlle⁴  Yann Le Strat²  Thomas Hanslik¹  Thierry Blanchon³  Clément Turbelin³  Cécile Souty³ 

[1] Université Versailles Saint-Quentin-en-Yvelines, Versailles F-78000, France;Département des maladies infectieuses, Institut de Veille Sanitaire (InVS), St Maurice F-94415, France;Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Institut Pierre Louis d’Epidémiologie et de Santé Publique, Paris F-75012, France;AP-HP, Hôpital Saint-Antoine, unité de santé publique, Paris F-75012, France

关键词: Volume of consultations;    Adjustment;    Incidence estimation;    Sentinel network;    General practitioners;    Surveillance;   

Others  :  1139732
DOI  :  10.1186/s12963-014-0019-8

 received in 2013-11-18, accepted in 2014-07-09,  发布年份 2014

【 摘 要 】

Background

In primary care surveillance systems based on voluntary participation, biased results may arise from the lack of representativeness of the monitored population and uncertainty regarding the population denominator, especially in health systems where patient registration is not required.

Methods

Based on the observation of a positive association between number of cases reported and number of consultations by the participating general practitioners (GPs), we define several weighted incidence estimators using external information on consultation volume in GPs. These estimators are applied to data reported in a French primary care surveillance system based on voluntary GPs (the Sentinelles network) for comparison.

Results

Depending on hypotheses for weight computations, relative changes in weekly national-level incidence estimates up to 3% for influenza, 6% for diarrhea, and 11% for varicella were observed. The use of consultation-weighted estimates led to bias reduction in the estimates. At the regional level (NUTS2 level - Nomenclature of Statistical Territorial Units Level 2), relative changes were even larger between incidence estimates, with changes between -40% and +55%. Using bias-reduced weights decreased variation in incidence between regions and increased spatial autocorrelation.

Conclusions

Post-stratification using external administrative data may improve incidence estimates in surveillance systems based on voluntary participation.

【 授权许可】

   
2014 Souty et al.; licensee BioMed Central Ltd.

【 图 表 】

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