Predicting Opioid Overdose Deaths Using Prescription Drug Monitoring Program Data
Predicting Opioid Overdose Deaths Using Prescription Drug Monitoring Program Data
复制标题
DOI：
10.1016/j.amepre.2019.07.026
复制
发表时间：
2019-12-01
影响因子：
5.5
通讯作者：
Weiner, Jonathan P.
中科院分区：
文献类型：
--
作者：
Ferris, Lindsey M.;Saloner, Brendan;Weiner, Jonathan P.
简介：处方药监测计划数据可以提供患者阿片类药物过量可能性的见解，但临床医生和公共卫生官员缺乏准确识别最高风险个体的指标。利用处方药监测项目的处方历史，开发并验证了一个预测模型，以确定那些由于任何阿片类药物或非法阿片类药物而有致命过量风险的人。方法：2018年12月至2019年7月，对2016年1月至6月服用阿片类药物处方的18-80岁马里兰州居民（n=565,175）进行回顾性队列分析。从首席法医办公室确定了致命的阿片类药物过量，并在个人层面上与处方药监测方案数据联系起来。采用对半分割技术开发并验证了具有6个月回顾期的多变量逻辑回归，并评估了模型校准和判别。结果：任何阿片类药物相关致命过量的预测因素包括男性、65-80岁、医疗补助、医疗保险、1次或1次以上长效阿片类药物、1次或1次以上丁丙诺啡、2至3次和4次或更多短效II类阿片类药物、阿片类药物供应日>= 91天、平均吗啡毫克当量日剂量、2次或2次以上苯二氮卓类药物和1次或1次以上肌肉松弛剂。验证队列的模型判别性良好（曲线下面积：任意，0.81；非法，0.77）。结论：利用处方药监测项目数据，建立了预测阿片类药物过量致死的模型。鉴于最近涉及海洛因和芬太尼的死亡在全国流行，值得注意的是，该模型在确定非法和处方类阿片有过量死亡风险的人方面表现同样良好。(C) 2019美国预防医学杂志。Elsevier Inc.出版。版权所有。
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 look-back period and assessed model calibration and discrimination.Results: Predictors of any opioid-related fatal overdose included male sex, age 65-80 years, Medicaid, Medicare, 1 or more long-acting opioid fills, 1 or more buprenorphine fills, 2 to 3 and 4 or more short-acting schedule II opioid fills, opioid days' supply >= 91 days, average morphine milligram equivalent daily dose, 2 or more benzodiazepine fills, and 1 or more muscle relaxant fills. Model discrimination for the validation cohort was good (area under the curve: any, 0.81; illicit, 0.77).Conclusions: A model for predicting fatal opioid overdoses was developed using Prescription Drug Monitoring Program data. Given the recent national epidemic of deaths involving heroin and fentanyl, it is noteworthy that the model performed equally well in identifying those at risk for overdose deaths from both illicit and prescription opioids. (C) 2019 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.