A Tool to Assess Risk of De Novo Opioid Abuse or Dependence
A Tool to Assess Risk of De Novo Opioid Abuse or Dependence
复制标题
DOI：
10.1016/j.amjmed.2016.02.014
复制
发表时间：
2016-07-01
影响因子：
5.9
通讯作者：
Gage, Brian F.
中科院分区：
文献类型：
--
作者：
Ciesielski, Thomas;Iyengar, Reethi;Gage, Brian F.
背景技术背景：确定阿片类药物滥用或依赖的风险因素将有助于临床医生实践知情处方，并可能有助于减轻阿片类药物滥用或依赖。本研究的目的是确定预测阿片类药物滥用或dependence.METHODS的变量：一项回顾性队列研究，使用去识别的综合药房和医疗索赔进行了2009年10月至2013年9月。确定了在索引期内至少有1次阿片类药物处方声明（索引声明）的患者。我们使用指数索赔前12个月的数据（前期）确定风险因素，并使用指数索赔后12个月的数据（后期）捕获滥用或依赖诊断。我们纳入了18岁或以上的连续合格（前期和后期）商业保险患者。我们排除了患有癌症、长期居住在护理机构或既往诊断为阿片类药物滥用或依赖的患者（由国际疾病分类第9版代码或前期丁丙诺啡/纳洛酮声明确定）。结果是阿片类药物滥用（国际疾病分类第9次修订代码304.0x）或依赖（305.5）的诊断。在2067例患者（0.3%）中观察到阿片类药物滥用或依赖。有几个因素可以预测阿片类药物滥用或依赖：（每十年[老年人]比值比[OR]，0.68）;长期阿片类药物使用者（OR，4.39）;精神疾病史（OR，3.45）;非阿片类药物滥用（OR，2.82）;酒精滥用（OR，2.37）;高吗啡等效剂量/日用户（OR，1.98）;烟草使用（OR，1.80）;从多个处方者处获得阿片类药物（1.71）居住在南方（OR，1.65），西（OR，1.49）或中西部（OR，1.24）;使用多个药房（OR，1.59）;男性（OR，1.43）;增加30天调整后的阿片类药物处方结论：容易获得的人口统计学、临床、行为、药学和地理信息可用于预测阿片类药物滥用或依赖的可能性。(C)2016 Elsevier Inc. All rights reserved.
BACKGROUND: Determining risk factors for opioid abuse or dependence will help clinicians practice informed prescribing and may help mitigate opioid abuse or dependence. The purpose of this study is to identify variables predicting opioid abuse or dependence.METHODS: A retrospective cohort study using de-identified integrated pharmacy and medical claims was performed between October 2009 and September 2013. Patients with at least 1 opioid prescription claim during the index period (index claim) were identified. We ascertained risk factors using data from 12 months before the index claim (pre-period) and captured abuse or dependency diagnosis using data from 12 months after the index claim (postperiod). We included continuously eligible (pre- and postperiod) commercially insured patients aged 18 years or older. We excluded patients with cancer, residence in a long-term care facility, or a previous diagnosis of opioid abuse or dependence (identified by International Classification of Diseases 9th revision code or buprenorphine/naloxone claim in the pre-period). The outcome was a diagnosis of opioid abuse (International Classification of Diseases 9th revision code 304.0x) or dependence (305.5).RESULTS: The final sample consisted of 694,851 patients. Opioid abuse or dependence was observed in 2067 patients (0.3%). Several factors predicted opioid abuse or dependence: younger age (per decade [older] odds ratio [OR], 0.68); being a chronic opioid user (OR, 4.39); history of mental illness (OR, 3.45); nonopioid substance abuse (OR, 2.82); alcohol abuse (OR, 2.37); high morphine equivalent dose per day user (OR, 1.98); tobacco use (OR, 1.80); obtaining opioids from multiple prescribers (OR, 1.71); residing in the South (OR, 1.65), West (OR, 1.49), or Midwest (OR, 1.24); using multiple pharmacies (OR, 1.59); male gender (OR, 1.43); and increased 30-day adjusted opioid prescriptions (OR, 1.05).CONCLUSIONS: Readily available demographic, clinical, behavioral, pharmacy, and geographic information can be used to predict the likelihood of opioid abuse or dependence. (C) 2016 Elsevier Inc. All rights reserved.