Paralysis Analysis: Investigating Paralysis Visit Anomalies in New Jersey

• DOI: 10.5210/ojphi.v5i1.4441
• Publication Date: 2013-04-23T21:14:35Z
• Authors: Teresa Hamby; Stella Tsai; Carol Genese; Andrew Walsh; Lauren Bradford; Edward Lifshitz
• Keywords: 03 medical and health sciences; 0302 clinical medicine; 3. Good health

The NJ Department of Health's syndromic surveillance system developed an algorithm to categorize heat-related illness (HRI) based on a patient's chief complaint during an emergency room visit, then matched these data with subsequent Uniform Billing (UB) diagnosis data. The overall sensitivity of the algorithm was 16% and the positive predictive value was 40%. Evaluation of a major heat event found both the sensitivity and positive predictive value increased to about 23% and 60%, respectively. While the HRI algorithm was relatively insensitive, sensitivity improved during major heat events and all excursions in HRI were identified using chief complaint data.