Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA, USA; Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, 401 Parnassus, Box 0984, San Francisco 94143, USA.
Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, 401 Parnassus, Box 0984, San Francisco 94143, USA.
Prev Med. 2018 May;110:31-37. doi: 10.1016/j.ypmed.2018.01.019. Epub 2018 Feb 2.
Strategies are needed to identify at-risk patients for adverse events associated with prescription opioids. This study identified prescription opioid misuse in an integrated health system using electronic health record (EHR) data, and examined predictors of misuse and overdose. The sample included patients from an EHR-based registry of adults who used prescription opioids in 2011 in Kaiser Permanente Northern California, a large integrated health care system. We characterized time-at-risk for opioid misuse and overdose, and used Cox proportional hazard models to model predictors of these events from 2011 to 2014. Among 396,452 patients, 2.7% were identified with opioid misuse and 1044 had an overdose event. Older patients were less likely to meet misuse criteria or have an overdose. Whites were more likely to be identified with misuse, but not to have an overdose. Alcohol and drug disorders were related to higher risk of misuse and overdose, with the exception that marijuana disorder was not related to opioid misuse. Higher daily opioid dosages and benzodiazepine use increased the risk of both opioid misuse and overdose. We characterized several risk factors associated with misuse and overdose using EHR-based data, which can be leveraged relatively quickly to inform preventive strategies to address the opioid crisis.
需要制定策略来识别与处方类阿片相关不良事件相关的高危患者。本研究使用电子健康记录 (EHR) 数据在一个综合医疗系统中确定了处方类阿片滥用情况，并研究了滥用和过量用药的预测因素。该样本包括来自 Kaiser Permanente Northern California 的基于 EHR 的成年人处方类阿片使用者注册表的患者，这是一个大型综合医疗保健系统。我们描述了阿片类药物滥用和过量用药的风险期，并使用 Cox 比例风险模型来模拟 2011 年至 2014 年这些事件的预测因素。在 396452 名患者中，有 2.7%被确定为阿片类药物滥用，有 1044 人发生了过量用药事件。年龄较大的患者不太可能符合滥用标准或发生过量用药。白人更有可能被确定为滥用，但不会发生过量用药。酒精和药物障碍与更高的滥用和过量用药风险相关，但大麻障碍与阿片类药物滥用无关。更高的每日阿片类药物剂量和苯二氮䓬类药物使用增加了阿片类药物滥用和过量用药的风险。我们使用基于 EHR 的数据描述了与滥用和过量用药相关的几个风险因素，这些因素可以相对较快地利用起来，为解决阿片类药物危机提供预防策略。
