Background Health systems may play an important role in identification of patients at-risk of opioid medication overdose. However, standard measures for identifying overdose risk in administrative data do not exist. Objective Examine the association between opioid medication overdose and 2 validated measures of non-medical use of prescription opioids within claims data. Research Design A longitudinal retrospective cohort study that estimated associations between overdose and non-medical use. Subjects Adult Pennsylvania Medicaid program 2007-2012 patients initiating opioid treatment who were: non-dual eligible, without cancer diagnosis, and not in long-term care facilities or receiving hospice. Measures Overdose (International Classification of Disease, 9th edition, prescription opioid poisonings codes), opioid abuse (opioid use disorder diagnosis while possessing an opioid prescription), opioid misuse (a composite indicator of number of opioid prescribers, number of pharmacies, and days supplied), and dose exposure during opioid treatment episodes. Results A total of 372,347 Medicaid enrollees with 583,013 new opioid treatment episodes were included in the cohort. Opioid overdose was higher among those with abuse (1.5%) compared to those without (0.2%, p<0.001). Overdose was higher among those with probable (1.8%) and possible (0.9%) misuse compared to those without (0.2%, p<0.001). Abuse (adjusted rate ratio [ARR]=1.52, 95% CI=1.10-2.10), probable misuse (ARR=1.98, 95% CI=1.46-2.67), and possible misuse (ARR=1.76, 95% CI=1.48-2.09) were associated with significantly more events of opioid medication overdose compared to those without. Conclusions Claims-based measures can be employed by health systems to identify individuals at-risk of overdose who can be targeted for restrictions on opioid prescribing, dispensing, or referral to treatment.

Author Contributions: Drs Kazi and Bibbins-Domingo had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

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