Kraus Sarah K, Sen Sanchita, Murphy Michelle, Pontiggia Laura
PharmD, BCPS, BCOP. Clinical Pharmacy Specialist- Hematology/Oncology, Pennsylvania Hospital. Philadelphia, PA (United States).
PharmD, BCPS. Clinical Pharmacy Specialist- Internal Medicine, Cooper University Hospital; & Associate Professor of Clinical Pharmacy, University of the Sciences. Philadelphia, PA (United States).
Pharm Pract (Granada). 2017 Apr-Jun;15(2):901. doi: 10.18549/PharmPract.2017.02.901. Epub 2017 Jun 30.
To evaluate the impact of a pharmacy-technician centered medication reconciliation (PTMR) program by identifying and quantifying medication discrepancies and outcomes of pharmacist medication reconciliation recommendations.
A retrospective chart review was performed on two-hundred patients admitted to the internal medicine teaching services at Cooper University Hospital in Camden, NJ. Patients were selected using a stratified systematic sample approach and were included if they received a pharmacy technician medication history and a pharmacist medication reconciliation at any point during their hospital admission. Pharmacist identified medication discrepancies were analyzed using descriptive statistics, bivariate analyses. Potential risk factors were identified using multivariate analyses, such as logistic regression and CART. The priority level of significance was set at 0.05.
Three-hundred and sixty-five medication discrepancies were identified out of the 200 included patients. The four most common discrepancies were omission (64.7%), non-formulary omission (16.2%), dose discrepancy (10.1%), and frequency discrepancy (4.1%). Twenty-two percent of pharmacist recommendations were implemented by the prescriber within 72 hours.
A PTMR program with dedicated pharmacy technicians and pharmacists identifies many medication discrepancies at admission and provides opportunities for pharmacist reconciliation recommendations.
通过识别和量化用药差异以及药剂师用药核对建议的结果,评估以药房技术员为中心的用药核对(PTMR)计划的影响。
对新泽西州卡姆登库珀大学医院内科教学服务收治的200例患者进行回顾性病历审查。采用分层系统抽样方法选择患者,如果他们在住院期间的任何时间接受了药房技术员的用药史和药剂师的用药核对,则纳入研究。使用描述性统计、双变量分析对药剂师识别出的用药差异进行分析。使用多变量分析,如逻辑回归和分类与回归树(CART),识别潜在风险因素。显著性的优先水平设定为0.05。
在纳入研究的200例患者中,共识别出365处用药差异。最常见的四类差异为遗漏(64.7%)、非处方遗漏(16.2%)、剂量差异(10.1%)和频次差异(4.1%)。22%的药剂师建议在72小时内得到了开处方者的执行。
由专业药房技术员和药剂师参与的PTMR计划在入院时识别出许多用药差异,并为药剂师的核对建议提供了机会。