Smith Perry

The Centers for Disease Control and Prevention BioSense has developed chief complaint (CC) and ICD9 sub syndrome classifiers for the major syndromes for early event detection and situational awareness. The prevalence of these sub-syndromes in the emergency department population and the performance of these CC classifiers have been little studied. Chart reviews have been used in the past to study this type of question but because of the large number of cases to review, the labor involved would be prohibitive. Therefore, we used an ICD9 code classifier for a syndrome as a surrogate by chart reviews to estimate the performance of a CC classifier.

Objective

To determine the prevalence of the sub-syndromes based on the ICD9 classifiers, and to determine the sensitivity, specificity, positive predictive value and negative predictive value of CC classifiers for the sub-syndromes associated with the respiratory and gastrointestinal syndromes using the ICD9 classifier as the criterion standard.

The Centers for Disease Control and Prevention BioSense project has developed chief complaint (CC) and ICD9 sub-syndrome classifiers for the major syndromes for early event detection and situational awareness. This has the potential to expand the usefulness of syndromic surveillance, but little data exists evaluating this approach. The overall performance of classifiers can differ significantly among syndromes, and presumably among subsyndromes as well. Also, we had previously found that the seasonal pattern of diarrhea was different for patients < 60 months of age (younger) and for patients > 60 months of age (older).

Objective

Using chart review as the criterion standard to estimate the sensitivity, specificity, positive predictive value and negative predictive value of New York State hospital emergency department CC classifiers for patients < 60 months of age and > 60 months of age for the gastrointestinal (GI) syndrome and the following GI sub-syndromes: “abdominal pain”, “nausea-vomiting” and “diarrhea”.

The existing New York State Department of Health emergency department syndromic surveillance system has used patient’s chief complaint (CC) for assigning to six syndrome categories (Respiratory, Fever, Gastrointestinal, Neurological, Rash, Asthma). The sensitivity and specificity of the CC computer algorithms that assign CC to syndrome categories are determined by using chart review as the criterion standard. These analyses are used to refine the algorithm and to evaluate the effect of changes in the syndrome definitions. However, the chart review (CR) method is labor intensive and expensive. Using an automated ICD9 code-based assignment as a surrogate for chart review could offer a significant cost reduction in this process and allow us to survey a much larger sample of visits.

To evaluate four algorithms with varying baseline periods and adjustment for day of week for anomaly detection in syndromic surveillance data.