Kirsten Vannice1,2, Julia Hood2, Nicole Yarid2, Meagan Kay2, Richard Harruff2, Jeff Duchin2. 1. 1242 Epidemiology Workforce Branch, Division of Scientific Education and Professional Development, Epidemic Intelligence Service, Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA. 2. 7285 Prevention Division, Public Health-Seattle & King County, Seattle, WA, USA.
Abstract
OBJECTIVES: Up-to-date information on the occurrence of drug overdose is critical to guide public health response. The objective of our study was to evaluate a near-real-time fatal drug overdose surveillance system to improve timeliness of drug overdose monitoring. METHODS: We analyzed data on deaths in the King County (Washington) Medical Examiner's Office (KCMEO) jurisdiction that occurred during March 1, 2017-February 28, 2018, and that had routine toxicology test results. Medical examiners (MEs) classified probable drug overdoses on the basis of information obtained through the death investigation and autopsy. We calculated sensitivity, positive predictive value, specificity, and negative predictive value of MEs' classification by using the final death certificate as the gold standard. RESULTS: KCMEO investigated 2480 deaths; 1389 underwent routine toxicology testing, and 361 were toxicologically confirmed drug overdoses from opioid, stimulant, or euphoric drugs. Sensitivity of the probable overdose classification was 83%, positive predictive value was 89%, specificity was 96%, and negative predictive value was 94%. Probable overdoses were classified a median of 1 day after the event, whereas the final death certificate confirming an overdose was received by KCMEO an average of 63 days after the event. CONCLUSIONS: King County MEs' probable overdose classification provides a near-real-time indicator of fatal drug overdoses, which can guide rapid local public health responses to the drug overdose epidemic.
OBJECTIVES: Up-to-date information on the occurrence of drug overdose is critical to guide public health response. The objective of our study was to evaluate a near-real-time fatal drug overdose surveillance system to improve timeliness of drug overdose monitoring. METHODS: We analyzed data on deaths in the King County (Washington) Medical Examiner's Office (KCMEO) jurisdiction that occurred during March 1, 2017-February 28, 2018, and that had routine toxicology test results. Medical examiners (MEs) classified probable drug overdoses on the basis of information obtained through the death investigation and autopsy. We calculated sensitivity, positive predictive value, specificity, and negative predictive value of MEs' classification by using the final death certificate as the gold standard. RESULTS: KCMEO investigated 2480 deaths; 1389 underwent routine toxicology testing, and 361 were toxicologically confirmed drug overdoses from opioid, stimulant, or euphoric drugs. Sensitivity of the probable overdose classification was 83%, positive predictive value was 89%, specificity was 96%, and negative predictive value was 94%. Probable overdoses were classified a median of 1 day after the event, whereas the final death certificate confirming an overdose was received by KCMEO an average of 63 days after the event. CONCLUSIONS: King County MEs' probable overdose classification provides a near-real-time indicator of fatal drug overdoses, which can guide rapid local public health responses to the drug overdose epidemic.
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