Using Local Toxicology Data for Drug Overdose Mortality Surveillance
AbstractObjectiveTo describe the potential impact of using toxicology data to supportdrug overdose mortality surveillance.IntroductionAlthough Marin County ranks as the healthiest county in California,it ranks poorly in substance abuse indicators, including drug overdosemortality.1Death certificates do not always include specific detail onthe substances involved in a drug overdose.2This lack of specificitymakes it difficult to identify public health issues related to specificprescription drugs in our community. We analyzed 2013 drugoverdose death toxicology reports to determine if they could improvethe description of drug overdose deaths in our community and todescribe associated data characteristics.MethodsToxicology reports were requested from the Office of the Sheriff-Coroner for 37 drug overdose deaths among Marin County residents,comprising 95% of the 39 total drug overdose deaths in 2013.The remaining two deaths were excluded as they were associated withinhalation of therapeutic gases. Select information from toxicologyreports was entered into a database for aggregate analyses. Drugoverdose deaths were considered “fully detailed” if they included thespecific types of drugs involved in the death and did not use any broadlanguage to describe the death (i.e. narcotic, multiple drugs). Student’sT-tests (α=0.05) were used to identify significant differences betweengroups of interest.ResultsOf the 37 drug poisoning deaths analyzed, 34 (92%) had availabletoxicology information. The remaining three (8%) deaths occurredoutside of Marin County and were thus investigated by anotherjurisdiction. A basic toxicology panel was ordered on 17 (50%) ofthe 34 drug overdose deaths, while an expanded toxicology panelwas ordered on the remaining 17 (50%). Alcohol was identified inthe toxicology screen of 15 (44%); Amphetamines were identifiedin 8 (24%); and opiates were identified in 25 (74%) drug overdosedeaths. Among the 25 deaths with at least one opiate identified on thetoxicology screen, the majority (52%, n=13) also had alcohol present.The majority of drug overdose deaths, 18 (53%), did not have fullinformation about the type of drug involved. The average numberof drugs identified on the toxicology screen of all 34 drug overdosedeaths was 6 (SD: 3). The average number of drugs identified in thetoxicology screen significantly differed (p=0.0001) between causes ofdeath that were fully detailed (Mean: 4; 95% CI: 3-5) and those thatwere not fully detailed (Mean: 8; 95% CI: 7-10).ConclusionsData from the Sheriff-Coroner’s office provided detail on thetypes of drugs involved in overdose deaths; however, it is difficultfor local public health practitioners to make decisions about causalityor contributions of these drugs to the death. These data may beuseful in understanding the difference between fully detailed andnon-detailed drug overdose deaths, and a broader context of drugcombinations associated with these deaths. Less drugs were identifiedin the toxicology screen of deaths that were fully detailed, suggestingthat overdose deaths that are not fully detailed may be exceedinglycomplex, making it difficult for medical examiners and coroners toassess causality. Approximately three-quarters of 2013 drug overdosedeaths contained opiates on the toxicology screen, indicating thatopiates may be a significant contributor to overdose deaths in ourcommunity. Our results are descriptive in nature; therefore, eventhough alcohol or opiates were identified on the toxicology screen,they may not be responsible for the overdose death. Given that overhalf of our 2013 overdose deaths were not fully detailed with drugtype, local jurisdictions should work closely with their corner and/ormedical examiner to fully detail death certificates with drugs involvedin overdose deaths.
How to Cite
Hannah, H. A., Arambula, K., Ereman, R., Harris, D., Torres, A., & Willis, M. (2017). Using Local Toxicology Data for Drug Overdose Mortality Surveillance. Online Journal of Public Health Informatics, 9(1). https://doi.org/10.5210/ojphi.v9i1.7733
Non-Infectious Disease Surveillance Use Cases