Using a theoretical predictive tool for the analysis of recent health department inspections at outbreak restaurants and relation of this information to foodborne illness likelihood.

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Because U.S. restaurants are inspected at least annually against criteria in the U.S. Food and Drug Administration Model Food Code, large amounts of data are generated and should be systematically reviewed. The purpose of this study was to determine the relationships among the data obtained through health department inspections, the contributing factors to foodborne illness identified by the Centers for Disease Control and Prevention, and the risks of outbreaks of norovirus, Salmonella, and Clostridium perfringens infection associated with a specific restaurant. These agents were chosen for the analysis because they cause the majority of foodborne illnesses. A theoretical predictive assessment tool was built that extracts data from routine health department inspection reports for specific restaurants to establish a risk profile for each restaurant and identify the likelihood of a norovirus, Salmonella, or C. perfringens outbreak at that restaurant. The tool was used to examine inspection reports from restaurants known to have had confirmed norovirus, Salmonella, and C. perfringens outbreaks. Although evaluation of an extensive data set revealed lack of an overall association between outbreak inspection scores and routine inspection scores obtained at outbreak restaurant locations, certain specific violations were significantly more likely to be recorded. Significant differences in types of violations recorded during outbreak and routine inspections were determined. When risks based on violation type can be identified, targeted actions may be able to be prioritized and implemented to help decrease illnesses.