Evaluation of the performance of drug-drug interaction screening software in community and hospital pharmacies
Evaluation of the performance of drug-drug interaction screening software in community and hospital pharmacies
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DOI：
10.18553/jmcp.2006.12.5.383
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发表时间：
2006-06-01
影响因子：
--
通讯作者：
Armstrong, EP
中科院分区：
文献类型：
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作者：
Abarca, J;Col贸n, LR;Armstrong, EP
背景技术背景：计算机化药物相互作用（DDI）筛查被广泛用于在住院和门诊环境中识别潜在有害的药物组合。目的：评估药物相互作用（DDI）筛查软件在社区和医院药房计算机系统中识别选择临床显著DDI的性能。方法：2004年，图森大都会地区的10个社区药房和10个医院药房被邀请参加这项研究。为了测试药房使用的每个系统的性能，使用25种药物创建了6个模拟患者配置文件，其中包含37个药物-药物对，其中16个是对患者安全构成潜在风险的具有临床意义的DDI。将每个配置文件输入计算机药房系统，并记录每个药物对是否存在DDI警报的系统响应。计算每个系统将每个药物对正确分类为DDI或非DDI的正确响应百分比和灵敏度、特异性、阳性预测值和阴性预测值。这些措施的汇总统计分别计算社区和医院pharmacs.RESULTS：8个社区药房和5个医院药房在图森大都市区同意参加这项研究。社区药房的中位敏感性和中位特异性分别为0.88（范围，0.81 - 0.94）和0.91（范围，0.67-1.00）。对于医院药房，中位灵敏度和中位特异性为0.38（范围，0.15-0.94）和0.95（范围0.81-0.95）。基于1个大都市地区的8个社区药房和5个医院药房的便利样本，与2001年发表的研究相比，社区药房计算机系统在筛选DDI方面的性能在过去几年中似乎有所改善。然而，医院药房计算机系统的性能仍然存在显着差异，即使是由同一供应商制造的系统。未来的研究应该集中在提高这些系统的性能，准确和精确地识别DDI的高概率导致真正的潜在不良影响的临床结果，并创建一个低的“噪音”与假阳性警报的比率。
BACKGROUND: Computerized drug-drug interaction (DDI) screening is widely used to identify potentially harmful drug combinations in the inpatient and outpatient setting.OBJECTIVE: To evaluate the performance of drug-drug interaction (DDI) screening software in identifying select clinically significant DDIs in pharmacy computer systems in community and hospital pharmacies.METHODS: Ten community pharmacies and 10 hospital pharmacies in the Tucson metropolitan area were invited to participate in the study in 2004. To test the performance of each of the systems used by the pharmacies, 25 medications were used to create 6 mock patient profiles containing 37 drug-drug pairs, 16 of which are clinically meaningful DDIs that pose a potential risk to patient safety. Each profile was entered into the computer pharmacy system, and the system response in terms of the presence or absence of a DDI alert was recorded for each drug pair. The percentage of correct responses and the sensitivity, specificity, positive predictive value, and negative predictive value of each system to correctly classify each drug pair as a DDI or not was calculated. Summary statistics of these measures were calculated separately for community and hospital pharmacies.RESULTS: Eight community pharmacies and 5 hospital pharmacies in the Tucson metropolitan area agreed to participate in the study. The median sensitivity and median specificity for community pharmacies was 0.88 (range, 0.81 -0.94) and 0.91 (range, 0.67-1.00), respectively. For hospital pharmacies, the median sensitivity and median specificity was 0.38 (range, 0.15-0.94) and 0.95 (range, 0.81-0.95), respectively.CONCLUSION: Based on this convenience sample of 8 community pharmacies and 5 hospital pharmacies in 1 metropolitan area, the performance of community pharmacy computer systems in screening DDIs appears to have improved over the last several years compared with research published previously in 2001. However, significant variation remains in the performance of hospital pharmacy computer systems, even among systems manufactured by the same vendor. Future research should focus on improving the performance of these systems in accurately and precisely identifying DDIs with a high probability of resulting in true potential adverse effects on clinical outcomes and creating a low "noise" ratio associated with false-positive alerts.