Authors
Ferris, Saloner, Schneider Krawczyk, Jarman, Jackson, Lyons, Eisenberg, Richards, Lemke, Weiner
Publication date
2019
Journal
American Journal of Preventive Medicine
Volume
57
Issue
6
Pages
e211-e217
Description
Introduction
Prescription Drug Monitoring Program data can provide insights into a patient's likelihood of an opioid overdose, yet clinicians and public health officials lack indicators to identify individuals at highest risk accurately. A predictive model was developed and validated using Prescription Drug Monitoring Program prescription histories to identify those at risk for fatal overdose because of any opioid or illicit opioids.
Methods
From December 2018 to July 2019, a retrospective cohort analysis was performed on Maryland residents aged 18–80 years with a filled opioid prescription (n=565,175) from January to June 2016. Fatal opioid overdoses were identified from the Office of the Chief Medical Examiner and were linked at the person-level with Prescription Drug Monitoring Program data. Split-half technique was used to develop and validate a multivariate logistic regression with a 6-month lookback period and …
Total citations
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Scholar articles
LM Ferris, B Saloner, N Krawczyk, KE Schneider… - American journal of preventive medicine, 2019