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This paper offers an approach for governments to harness the information contained in social media in order to make public inspections and disclosure more efficient. As a case study, we turn to restaurant hygiene inspections – which are done for restaurants throughout the United States and in most of the world and are a frequently cited example of public inspections and disclosure. We present the first empirical study that shows the viability of statistical models that learn the mapping between textual signals in restaurant reviews and the hygiene inspection records from the Department of Public Health. The learned model achieves over 82% accuracy in discriminating severe offenders from places with no violation, and provides insights into salient cues in reviews that are indicative of the restaurant’s sanitary conditions. Our study suggests that public disclosure policy can be improved by mining public opinions from social media to target inspections and to provide alternative forms of disclosure to customers.

Preexisting or new-onset atrial fibrillation (AF) commonly occurs in patients with an acute coronary syndrome (ACS). However, it is currently unknown if previous or new-onset AF confers different risks in these patients. To determine the prognostic significance of new-onset and previous AF in patients with ACS, we evaluated all patients with ACS enrolled in the multinational Global Registry of Acute Coronary Events (GRACE) between April 1999 and September 2001. We compared clinical characteristics, management, and hospital outcomes in patients with ACS and new-onset and previous AF with those without AF. Of a total of 21,785 patients with ACS enrolled in GRACE, 1,700 (7.9%) had previous AF and 1,221 (6.2%) had new-onset AF. Patients with any AF were older, more likely to be women, had more co-morbid conditions, and worse hemodynamic status. Most in-hospital adverse events (reinfarction, shock, pulmonary edema, bleeding, stroke, and mortality) were significantly higher in patients with any AF than those without AF. Only new-onset AF (not previous AF) was an independent predictor of all adverse in-hospital outcomes. We conclude that compared with patients with ACS without any AF, previous and new-onset AF are associated with increased hospital morbidity and mortality. However, only new-onset AF is an independent predictor of in-hospital adverse events in patients with ACS.