Laurel Harduar Morano1, Sharon Watkins2,3. 1. 1 Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 2. 2 Bureau of Epidemiology, Pennsylvania Department of Health, Harrisburg, PA, USA. 3. 3 Public Health Research Unit, Florida Department of Health, Tallahassee, FL, USA.
Abstract
OBJECTIVES: The primary objective of this study was to identify patients with heat-related illness (HRI) using codes for heat-related injury diagnosis and external cause of injury in 3 administrative data sets: emergency department (ED) visit records, hospital discharge records, and death certificates. METHODS: We obtained data on ED visits, hospitalizations, and deaths for Florida residents for May 1 through October 31, 2005-2012. To identify patients with HRI, we used codes from the International Classification of Diseases, Ninth Revision, Clinical Modification ( ICD-9-CM) to search data on ED visits and hospitalizations and codes from the International Classification of Diseases, Tenth Revision ( ICD-10) to search data on deaths. We stratified the results by data source and whether the HRI was work related. RESULTS: We identified 23 981 ED visits, 4816 hospitalizations, and 140 deaths in patients with non-work-related HRI and 2979 ED visits, 415 hospitalizations, and 23 deaths in patients with work-related HRI. The most common diagnosis codes among patients were for severe HRI (heat exhaustion or heatstroke). The proportion of patients with a severe HRI diagnosis increased with data source severity. If ICD-9-CM code E900.1 and ICD-10 code W92 (excessive heat of man-made origin) were used as exclusion criteria for HRI, 5.0% of patients with non-work-related deaths, 3.0% of patients with work-related ED visits, and 1.7% of patients with work-related hospitalizations would have been removed. CONCLUSIONS: Using multiple data sources and all diagnosis fields may improve the sensitivity of HRI surveillance. Future studies should evaluate the impact of converting ICD-9-CM to ICD-10-CM codes on HRI surveillance of ED visits and hospitalizations.
OBJECTIVES: The primary objective of this study was to identify patients with heat-related illness (HRI) using codes for heat-related injury diagnosis and external cause of injury in 3 administrative data sets: emergency department (ED) visit records, hospital discharge records, and death certificates. METHODS: We obtained data on ED visits, hospitalizations, and deaths for Florida residents for May 1 through October 31, 2005-2012. To identify patients with HRI, we used codes from the International Classification of Diseases, Ninth Revision, Clinical Modification ( ICD-9-CM) to search data on ED visits and hospitalizations and codes from the International Classification of Diseases, Tenth Revision ( ICD-10) to search data on deaths. We stratified the results by data source and whether the HRI was work related. RESULTS: We identified 23 981 ED visits, 4816 hospitalizations, and 140 deaths in patients with non-work-related HRI and 2979 ED visits, 415 hospitalizations, and 23 deaths in patients with work-related HRI. The most common diagnosis codes among patients were for severe HRI (heat exhaustion or heatstroke). The proportion of patients with a severe HRI diagnosis increased with data source severity. If ICD-9-CM code E900.1 and ICD-10 code W92 (excessive heat of man-made origin) were used as exclusion criteria for HRI, 5.0% of patients with non-work-related deaths, 3.0% of patients with work-related ED visits, and 1.7% of patients with work-related hospitalizations would have been removed. CONCLUSIONS: Using multiple data sources and all diagnosis fields may improve the sensitivity of HRI surveillance. Future studies should evaluate the impact of converting ICD-9-CM to ICD-10-CM codes on HRI surveillance of ED visits and hospitalizations.
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