Identifying Opioid Overdose Predictors using EHRs

“使用EHR识别阿片类药物过量预测因子” 疼痛和有效的疼痛管理是面临的最关键的健康问题之一 美国人2011年，医学研究所报告说， 美国人经历持续性疼痛，每年的医疗费用高达6350亿美元。 治疗和生产力损失。处方阿片类药物越来越多地用于治疗急性和 慢性疼痛迄今为止，定义阿片类药物相关不良事件（ADE）的流行病学研究 风险因素依赖于从诊断代码得出的广泛的、静态的风险分类。 这些研究虽然是重要的基础性工作，但也有三个重要的局限性：（1） 只关注最具灾难性的ADE（过量），因此错过了识别 轻度前驱ADE（如疲劳、头晕、嗜睡、过度镇静），可能 提前和预测过量;（2）它们不能可靠地捕获异常药物相关行为 （ADRB）-可能影响过量风险的风险使用模式;（3）它们依赖于临床医生- 结构化数据中的编码诊断，其灵敏度和特异性众所周知地弱，以及 忽视来自非结构化临床叙述的丰富阿片类药物相关信息。为了弥补这一差距， 我们提出了一种逐步的方法，利用电子健康记录的力量， 探索前驱不良事件，ADRB， 还有吸毒过量这种方法对下一代阿片类药物过量的发展至关重要 预防工具。

"Identifying Opioid Overdose Predictors using EHRs" Pain and effective pain management are among the most critical health issues facing Americans. In 2011, the Institute of Medicine reported that as many as one-third of all Americans experience persistent pain at an annual cost of as much as $635 billion in medical treatment and lost productivity. Prescription opioids are increasingly used to treat acute and chronic pain. To date, epidemiologic research defining opioid-related adverse drug event (ADE) risk factors has relied on broad, static categorizations of risk derived from diagnostic codes. Though important foundational work, these studies have three important limitations: (1) they focus on only the most catastrophic ADE (overdose) and thus miss the opportunity to identify less severe, prodromal ADEs (e.g. fatigue, dizziness, sleepiness, over-sedation) that may precede and predict overdose; (2) they do not reliably capture aberrant drug-related behaviors (ADRBs)—risky patterns of use that may affect overdose risk; and (3) they rely on clinician- coded diagnoses in structured data, which have notoriously weak sensitivity and specificity, and neglect rich opioid-related information from unstructured clinical narratives. To address this gap, we propose a stepwise approach that leverages the power of electronic health records and new computational methdologies to explore associations among prodromal adverse events, ADRBs, and overdose. This approach is critical to the development of next-generation opioid overdose prevention tools.