Abstract
Background: Accurate classification of intentional death as suicide is essential to target prevention measures appropriately. Unfortunately, manner of death (MOD) for many opioid-related fatalities are unclassified in the United States, and in Maryland, as many as 82% of overdose deaths are classified as undetermined manner. Aims: For opioid-related fatalities in Maryland, leverage death certificate data to develop a model for identifying suicide as MOD among those classified as undetermined by the medical examiner. Method: Demographic and toxicology data were used to develop a classification model for opioid-related deaths where MOD was known, and then applied to a cohort where MOD was undetermined to estimate the likelihood that the intent was suicide. Results: Antidepressants, neuroleptics, oxycodone, benzodiazepines, and acetaminophen were more common in deaths classified as suicide while fentanyl, cocaine, and morphine were more common among accidental deaths. Our classification model correctly identified suicide cases 82% of the time (PPV = 0.82; AUC = 0.90) and expanded the number of suicide cases by 43% when applied to undetermined deaths. Limitations: The accuracy and completeness of death records. Conclusions: Data from standard autopsies can be used to detect additional suicide deaths with good statistical precision. Incorporating clinical information could enhance predictive accuracy and improve classification.