METHODS: BioSense 2.0 phpMyAdmin was used to extract emergency department and inpatient hospital data from participating Maricopa County hospitals. Four syndrome definitions (i.e., “heat, specific”, sunburn, dehydration, and “heat, broad”) were used to search for patient records from 2015 with relevant diagnosis codes and/or chief complaint text. For each syndrome, cases were plotted over time by MMWR week. The “heat, specific” query was modeled after the “heat, excessive” query in BioSense, but added exclusion terms to remove records that were not related to environmental heat exposure (e.g., those complaining of “pain, swelling, and heat”). The sunburn and dehydration queries identified patients with clinical diagnoses or chief complaint terms related to either condition. The “heat, broad” query was designed to be extremely sensitive for identifying any patient directly or indirectly impacted by heat. The broad query retrieved records that met the criteria for “heat, specific”, sunburn, or dehydration, and those with more general symptoms, such as dizziness, light-headedness, or weakness.
RESULTS: Each query produced vastly different numbers of patient records [“heat, specific” (N=687), sunburn (N=191), dehydration (N=12,658), and “heat, broad” (N=72,245); not mutually exclusive]. The “heat, specific” and sunburn queries closely followed Maricopa County’s heat season with an upward trend beginning in May and a downward trend in October. The patterns produced by the dehydration and “heat, broad” queries did not trend with Arizona’s heat season.
CONCLUSIONS: With a very specific heat-related illness syndrome, the true burden of extreme heat exposure may be overlooked. This project helped demonstrate the potential utility for using alternate definitions for heat syndromic surveillance. The next steps of this project will be to manually review the data to refine the syndrome definitions and to determine which heat syndrome most closely correlates with environmental temperatures in the region.