Syndromic Surveillance of Acute Gastroenteritis Using the French Health Insurance Database: Discriminatory Algorithm and Drug Prescription Practices Evaluations

Abstract

The French national public health agency (Santé publique France) has used data from the national health insurance reimbursement system (SNDS) to identify medicalised acute gastroenteritis (mAGE) for more than 10 years. This paper presents the method developed to evaluate this system: performance and characteristics of the discriminatory algorithm, portability in mainland and overseas French departments, and verification of the mAGE database updating process. Pharmacy surveys with certified mAGE from 2012 to 2015 were used to characterise mAGE and to estimate the sensitivity and predictive positive value (PPV) of the algorithm. Prescription characteristics from these pharmacy surveys and from 2014 SNDS prescriptions in six mainland and overseas departments were compared. The sensitivity (0.90) and PPV (0.82) did not vary according to the age of the population or year. Prescription characteristics were similar within all studied departments. This confirms that the algorithm can be used in all French departments, for both paediatric and adult populations, with stability and durability over time. The algorithm can identify mAGE cases at a municipal level. The validated system has been implemented in a national waterborne disease outbreaks surveillance system since 2019 with the aim of improving the prevention of infectious disease risk attributable to localised tap water systems.

Early Detection and Monitoring of Gastrointestinal Infections Using Syndromic Surveillance: A Systematic Review

“…The 29 studies identified from the full screen included a range of different syndromic surveillance systems from ten countries and territories across Korea, United States, France, Sweden, Netherlands, Spain, Canada, United Kingdom, Japan, and Portugal. Just over half of the studies (52%, 15/29) were reported from the United States and United Kingdom [8,[12][13][14][15][16][17][18][19][20][21][22][23][24][25]. About 55% (16/29) [13,16,[22][23][24][25][26][27][28][29][30][31][32][33][34][35] of the studies indicated that syndromic surveillance exhibited the potential to detect GI infections earlier than traditional surveillance, while a further 10% (3/29) of studies indicated that syndromic surveillance exhibits the potential to detect GI infections or symptoms at an early stage but with limitations [15,20,36]; a further 3% (1/29) highlighted that syndromic surveillance exhibits potential to detect GI infections or symptoms at an early stage only when combined with traditional surveillance system [18].…”

“…The usefulness of syndromic surveillance in identifying GI infections or symptoms at an early stage was deemed unclear in 24% (7/29) of the included studies [8,12,17,19,21,37,38], while 2/29 of the included studies suggested that syndromic surveillance was incapable of detecting GI infections at an earlier stage in comparison to traditional surveillance [14,39].…”

“…While there is substantial evidence of the utility of syndromic surveillance for monitoring respiratory diseases in the community, such as influenza and respiratory syncytial virus [6], the utility of syndromic surveillance in GI infection surveillance is less clear. There is a smaller evidence base for its utility, and some of the published literature presents conflicting evidence [7,8]. Here, we report a systematic review which identifies and describes evidence of the utility of syndromic surveillance for the early detection and monitoring of GI infections.…”

Implementation of a national waterborne disease outbreak surveillance system: overview and preliminary results, France, 2010 to 2019

“…For the WBDO surveillance system, the SNDS is used to identify mAGE cases, defined as follows: any AGE case who consulted a general practitioner and purchased medications prescribed to treat AGE at a pharmacy within 2 days of the consultation. A specific algorithm built in 2011 and regularly updated is used to identify mAGE cases [18,19]. Cases are aggregated according to…”

Network Theory and Switching Behaviors: A User Guide for Analyzing Electronic Records Databases

“…There is no way for the physician to directly ascertain the compliance of the patient. However, drugs consumption can be inferred from administrative and medical databases, and although the prescription of a drug does not necessarily correspond to the consumption of that drug, it can be considered a good indicator [5,[20][21][22]. It is worth noting that statistical analysis of these kinds of databases is not straightforward because they are commonly characterized by records of tens of thousands of people (or more) for several years.…”