Department of Pharmacy Services, Houston Methodist Hospital, Houston, TX.
University of Houston College of Pharmacy, Houston, TX.
Am J Health Syst Pharm. 2019 Apr 8;76(8):530-536. doi: 10.1093/ajhp/zxz012.
The effectiveness of a systematic, streamlined approach to optimize drug-drug interaction alerts in an electronic health record for a health system was studied.
An 81-week quasi-experimental study was conducted to evaluate interventions made to medication-related clinical decision-support (CDS) alerts. Medication-related CDS alerts were systematically reduced using a multi disciplinary healthcare committee. The primary endpoint was weekly overall, modification, and acknowledgement rates of medication alerts after drug-drug interaction reclassification. Secondary endpoints included sub analysis of types of medication alerts (drug-drug interaction and duplicate therapy alerts) and alert use by providers (pharmacist and prescribers). Data was analyzed using interrupted time series regression analysis.
After implementation of the new alert system, total number of weekly inpatient alerts decreased from 68,900 (66,300-70,900) and 50,300 (48,600-53,600) in the postintervention period (p < 0.001). The perentage of alerts acknowledged weekly increased from 11.8% (IQR, 11.4-12.1%) in the preintervention period to 13.7% (IQR, 13.3-14.0%) in the postintervention period (p < 0.001). The percentage of alerts that were modified also increased from 5.0% (IQR, 4.9-5.3%) in the preintervention period to 7.3% (IQR, 7.0-7.6%) in the postintervention period (p < 0.001). Both increases were primarily seen with pharmacists versus other healthcare professionals (p < 0.001).
A committee-led systematic approach to optimizing drug-drug interactions facilitated a significant decrease in the overall number of alerts and an increase in both medication alert acknowledgement and modification rates.
研究了在电子健康记录中对药物-药物相互作用警报进行系统优化的方法，以提高医疗系统的效率。
进行了一项为期 81 周的准实验研究，以评估对与药物相关的临床决策支持（CDS）警报所采取的干预措施。通过多学科医疗委员会对与药物相关的 CDS 警报进行了系统地减少。主要终点是药物-药物相互作用重新分类后每周药物警报的整体、修改和确认率。次要终点包括药物警报（药物-药物相互作用和重复治疗警报）类型的子分析以及提供者（药剂师和处方者）对警报的使用。使用中断时间序列回归分析对数据进行分析。
在新警报系统实施后，每周住院患者的总警报数量从干预前的 68900（66300-70900）和 50300（48600-53600）降至 50300（48600-53600）（p < 0.001）。每周确认的警报百分比从干预前的 11.8%（IQR，11.4-12.1%）增加到干预后的 13.7%（IQR，13.3-14.0%）（p < 0.001）。修改的警报百分比也从干预前的 5.0%（IQR，4.9-5.3%）增加到干预后的 7.3%（IQR，7.0-7.6%）（p < 0.001）。这两个百分比的增加主要是由药剂师与其他医疗保健专业人员相比（p < 0.001）。
委员会主导的药物相互作用优化系统方法可显著减少警报总数，并提高药物警报的确认和修改率。
