用于确定长期护理机构用药暴露的药物索赔数据的有效性。

IF 2.4 4区 医学 Q3 PHARMACOLOGY & PHARMACY
Emma Pearce, Geraint Rogers, Lucy Carpenter, Maria C Inacio, Gillian E Caughey, Andrew Shoubridge, Lito Papanicolas, Janet K Sluggett
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引用次数: 0

摘要

目的:比较长期护理机构(LTCF)中个人的药物索赔和用药记录数据的准确性:对一项前瞻性队列研究(n = 279 名居民,5 家 LTCF)进行二次分析。研究人员从用药记录中提取了入院时定期用药的详细记录,并使用解剖治疗化学(ATC)分类代码进行了编码。将研究入组前 0-30、0-60、0-90、0-120 和 0-180 天内政府补贴药物的报销单与用药图表数据(参考标准)进行比较。确定了 3 位和 7 位 ATC 级别的敏感性、特异性、阳性预测值 (PPV) 和 95% CI:结果:共纳入了 149 名(占总人数的 53.4%)同时拥有用药记录和理赔数据的居民。使用 30 天和 180 天的报销单暴露窗,3 位数 ATC 级别药物的 PPV ≥ 75% 的比例分别为 89.4% 和 86.1%。在 120 天的报销单暴露窗口中,糖尿病药物、β-阻滞剂、钙通道阻滞剂、肾素-血管紧张素系统药物、抗帕金森药物、精神治疗药物和气道疾病药物的敏感性最高(均≥ 90%),维生素(1.4%,95% CI 0-7.7)和矿物质补充剂(10.3%,95% CI 2.9-24.2)的敏感性最低。除抗菌药和镇痛药外,每个暴露窗口内所有三位数级别药物的特异性均≥85%:结论:药品理赔数据在确定 LTCF 中处方药暴露方面具有很高的准确性。一般来说,90-120 天的暴露窗口足以确定暴露量,但大包装药物可能需要更长的暴露期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validity of Pharmaceutical Claims Data for Determining Medication Exposure in Long-Term Care Facilities.

Purpose: To compare the accuracy of pharmaceutical claims with medication administration chart data for individuals in long-term care facilities (LTCFs).

Methods: Secondary analyses of a prospective cohort study (n = 279 residents, 5 LTCFs) were conducted. Details of medications charted for regular administration at study enrollment were extracted from administration charts and coded using Anatomical Therapeutic Chemical (ATC) classification codes. Pharmaceutical claims for government-subsidized medications dispensed in the 0-30, 0-60, 0-90, 0-120, and 0-180 days before study enrollment were compared to medication chart data (reference standard). Sensitivity, specificity, and positive predictive value (PPV) and 95% CIs were determined at the 3- and 7-digit ATC levels.

Results: 149 (53.4% of total) residents with both medication chart and claims data available were included. The proportion of PPVs ≥ 75% for 3-digit ATC level medications was 89.4% and 86.1% using exposure windows of 30 and 180-days for claims, respectively. Using a 120-day exposure window for claims, sensitivity was highest for diabetes agents, beta-blocking agents, calcium channel blockers, agents acting on the renin-angiotensin system, anti-Parkinson drugs, psychoanaleptics, and airways disease agents (all ≥ 90%) and was lowest for vitamins (1.4%, 95% CI 0-7.7) and mineral supplements (10.3%, 95% CI 2.9-24.2). Specificity was ≥ 85% for all 3-digit level medications within each exposure window other than antibacterials and analgesics.

Conclusion: Pharmaceutical claims data has good accuracy for determining prescription medication exposure in LTCFs. Exposure windows of 90-120-days are generally sufficient for determining exposure although longer periods may be required for large pack sizes.

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来源期刊
CiteScore
4.80
自引率
7.70%
发文量
173
审稿时长
3 months
期刊介绍: The aim of Pharmacoepidemiology and Drug Safety is to provide an international forum for the communication and evaluation of data, methods and opinion in the discipline of pharmacoepidemiology. The Journal publishes peer-reviewed reports of original research, invited reviews and a variety of guest editorials and commentaries embracing scientific, medical, statistical, legal and economic aspects of pharmacoepidemiology and post-marketing surveillance of drug safety. Appropriate material in these categories may also be considered for publication as a Brief Report. Particular areas of interest include: design, analysis, results, and interpretation of studies looking at the benefit or safety of specific pharmaceuticals, biologics, or medical devices, including studies in pharmacovigilance, postmarketing surveillance, pharmacoeconomics, patient safety, molecular pharmacoepidemiology, or any other study within the broad field of pharmacoepidemiology; comparative effectiveness research relating to pharmaceuticals, biologics, and medical devices. Comparative effectiveness research is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition, as these methods are truly used in the real world; methodologic contributions of relevance to pharmacoepidemiology, whether original contributions, reviews of existing methods, or tutorials for how to apply the methods of pharmacoepidemiology; assessments of harm versus benefit in drug therapy; patterns of drug utilization; relationships between pharmacoepidemiology and the formulation and interpretation of regulatory guidelines; evaluations of risk management plans and programmes relating to pharmaceuticals, biologics and medical devices.
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