The economic burden of opioid poisoning in the United States and determinants of increased costs in opioid poisoning

Introduction: Opioid poisoning has been rapidly increasing in the past decade, and has been driven in large part due to increases in opioid prescribing. This has been accompanied by intervention efforts aimed at preventing and reversing opioid poisoning through naloxone prescription programs. Current literature have not quantified the economic burden of opioid poisoning. Understanding this information can help inform these efforts and bring light to this growing problem. In addition understanding various determinants of increased costs can help to identify the types of populations more likely to have greater costs.;Main Objectives: The objectives are 1) to quantify the economic burden of opioid poisoning, 2) to evaluate differences in costs, LOS, and in-hospital mortality depending on opioid type, 3) to identify opioids most likely to result in hospitalization for opioid-related ED visits and 4) to determine differences in the odds of admission to various hospital admission categories with respect to opioid type.;Methods: A cost-of-illness approach was used to estimate the economic burden of opioid poisoning. Direct costs and prevalence estimates were obtained from nationally representative databases. Other sources of direct costs were obtained from the literature. Indirect costs were measured using the human capital method. Differences in costs, LOS, and in-hospital mortality were measured through generalized linear models using the National Inpatient Sample in 2009 from the Healthcare Cost and Utilization Project. The Drug Abuse Warning Network database was used to evaluate opioids most likely to result in hospitalization and to evaluate the likelihood of different opioids to cause admission into different types of hospital settings.;Results: Opioid poisoning resulted in an economic burden approximately ;Conclusions: Opioid poisoning results in a significant economic burden to society. Costs, length of stay, in-patient mortality and the odds of hospitalization and admission type depend on the type of opioid involved. The results from this study can be used to inform policy efforts in providing interventions to reduce opioid poisoning and help focus efforts on populations at highest risk for increased costs.