Anesthesiology and Critical Care Medicine, Department of Anesthesiology, Division of Pain Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.
Pain Med. 2013 Dec;14(12):1900-7. doi: 10.1111/pme.12221. Epub 2013 Aug 15.
To identify and quantify the rate of aberrant drug-taking behaviors using objective data.
Institutional Review Board-approved anonymous, voluntary, quality improvement project.
University-based, multidisciplinary pain management center.
Consecutive initial visit patients.
Patients were interviewed, asked to provide a urine sample, and filled out a brief questionnaire about recent prescription, over-the-counter, and illicit drug use. Discrepancies between patient report (PQ), the Virginia State prescription monitoring program (PMP), referring physician records (MRs), and the point-of-care urine drug screen (POC UDS) results were scored from 0 (none) to a maximum of 2 points (2+ discrepancies) for each potential comparator between data sets. Maximum potential inconsistency score (IS) was 16 points.
Two hundred nine patients were interviewed to yield 118 specimens. Mean age of participants was 48.2 years (22-83 year); 65.3% were female. IS scores ranged from 1 to 11, and 52.5% of the patients had an IS ≥ 3. Higher IS scores correlated with higher numbers of pharmacies, prescribing physicians, prescriptions on the PMP, and presence of illicit substances in the urine. Addition of either POC UDS or PMP to PQ and MR increased identification of inconsistencies by >400%, and PMP plus UDS by >900%.
Patient report and the medical record are inadequate to screen for aberrant drug-related behaviors. Addition of PMP and POC UDS contribute significantly to identification of inconsistencies through higher IS scores and differentiate patients at higher risk of medication misuse, abuse, or diversion. Comparison of multiple sources of objective information provides better insight into inconsistencies of report and behavior, and may assist in more appropriate and safer prescribing decisions.
利用客观数据识别和量化异常药物使用行为的发生率。
机构审查委员会批准的匿名、自愿、质量改进项目。
基于大学的多学科疼痛管理中心。
连续的初始就诊患者。
对患者进行访谈，要求提供尿液样本，并填写一份关于近期处方药物、非处方药物和非法药物使用的简短问卷。患者报告（PQ）、弗吉尼亚州处方监测计划（PMP）、转介医生记录（MR）和即时尿液药物筛查（POC UDS）结果之间的差异从 0（无）到 2 分（2+差异）进行评分，每个数据集之间的潜在比较者均为 2 分。最大潜在不一致评分（IS）为 16 分。
对 209 名患者进行访谈，共获得 118 份标本。参与者的平均年龄为 48.2 岁（22-83 岁）；65.3%为女性。IS 评分范围为 1 至 11，52.5%的患者 IS≥3。较高的 IS 评分与更多的药店、处方医生、PMP 上的处方以及尿液中存在非法物质相关。将 POC UDS 或 PMP 添加到 PQ 和 MR 中，可将不一致的识别率提高 400%以上，而 PMP 加 UDS 则提高了 900%以上。
患者报告和医疗记录不足以筛查异常药物相关行为。添加 PMP 和 POC UDS 通过更高的 IS 评分，显著提高了不一致性的识别率，并区分了药物误用、滥用或转用风险较高的患者。比较多个客观信息来源可以更深入地了解报告和行为的不一致性，并可能有助于更适当和更安全的处方决策。
