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BMC Public Health. 2012; 12: 166.
Published online Mar 8, 2012. doi:  10.1186/1471-2458-12-166
PMCID: PMC3378465
Patient, physician, encounter, and billing characteristics predict the accuracy of syndromic surveillance case definitions
Geneviève Cadieux,corresponding author1 David L Buckeridge,#1,2 André Jacques,#3 Michael Libman,#4 Nandini Dendukuri,#1 and Robyn Tamblyn#1,4
1Department of Epidemiology and Biostatistics, McGill University, 1020 Pine Avenue West, Montreal, QC, H3A 1A2, Canada
2Direction de la Santé Publique de Montréal, 1301 Sherbrooke Street East, Montreal, QC, H2L 1M3, Canada
3Collège des Médecins du Québec, 2170 René-Lévesque Boulevard West, Montreal, QC, H3H 2T8, Canada
4Department of Medicine, McGill University, 3655 Sir William Osler Promenade, Montreal, QC, H3G 1Y6, Canada
corresponding authorCorresponding author.
#Contributed equally.
Geneviève Cadieux: genevieve.cadieux/at/mail.mcgill.ca; David L Buckeridge: david.buckeridge/at/mcgill.ca; André Jacques: ajacques/at/cmq.org; Michael Libman: michael.libman/at/muhc.mcgill.ca; Nandini Dendukuri: nandini.dendukuri/at/mcgill.ca; Robyn Tamblyn: robyn.tamblyn/at/mcgill.ca
Received September 5, 2011; Accepted March 8, 2012.
Abstract
Background
Syndromic surveillance systems are plagued by high false-positive rates. In chronic disease monitoring, investigators have identified several factors that predict the accuracy of case definitions based on diagnoses in administrative data, and some have even incorporated these predictors into novel case detection methods, resulting in a significant improvement in case definition accuracy. Based on findings from these studies, we sought to identify physician, patient, encounter, and billing characteristics associated with the positive predictive value (PPV) of case definitions for 5 syndromes (fever, gastrointestinal, neurological, rash, and respiratory (including influenza-like illness)).
Methods
The study sample comprised 4,330 syndrome-positive visits from the claims of 1,098 randomly-selected physicians working in Quebec, Canada in 2005-2007. For each visit, physician-facilitated chart review was used to assess whether the same syndrome was present in the medical chart (gold standard). We used multivariate logistic regression analyses to estimate the association between claim-chart agreement about the presence of a syndrome and physician, patient, encounter, and billing characteristics.
Results
The likelihood of the medical chart agreeing with the physician claim about the presence of a syndrome was higher when the treating physician had billed many visits for the same syndrome recently (ORper 10 visit, 1.05; 95% CI, 1.01-1.08), had a lower workload (ORper 10 claims, 0.93; 95% CI, 0.90-0.97), and when the patient was younger (ORper 5 years of age, 0.96; 95% CI, 0.94-0.97), and less socially deprived (ORmost versus least deprived, 0.76; 95% CI, 0.60-0.95).
Conclusions
Many physician, patient, encounter, and billing characteristics associated with the PPV of surveillance case definition are accessible to public health, and could be used to reduce false-positive alerts by surveillance systems, either by focusing on the data most likely to be accurate, or by adjusting the observed data for known biases in diagnosis reporting and performing surveillance using the adjusted values.
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