Czock David, Konias Michael, Seidling Hanna M, Kaltschmidt Jens, Schwenger Vedat, Zeier Martin, Haefeli Walter E
Department of Clinical Pharmacology and Pharmacoepidemiology, University Hospital Heidelberg, Heidelberg, Germany
Department of Clinical Pharmacology and Pharmacoepidemiology, University Hospital Heidelberg, Heidelberg, Germany.
J Am Med Inform Assoc. 2015 Jul;22(4):881-7. doi: 10.1093/jamia/ocv027. Epub 2015 Apr 24.
Electronic alerts are often ignored by physicians, which is partly due to the large number of unspecific alerts generated by decision support systems. The aim of the present study was to analyze critical drug prescriptions in a university-based nephrology clinic and to evaluate the effect of different alerting strategies on the alert burden.
In a prospective observational study, two advanced strategies to automatically generate alerts were applied when medication regimens were entered for discharge letters, outpatient clinic letters, and written prescriptions and compared to two basic reference strategies. Strategy A generated alerts whenever drug-specific information was available, whereas strategy B generated alerts only when the estimated glomerular filtration rate of a patient was below a drug-specific value. Strategies C and D included further patient characteristics and drug-specific information to generate even more specific alerts.
Overall, 1012 medication regimens were entered during the observation period. The average number of alerts per drug preparation in medication regimens entered for letters was 0.28, 0.080, 0.019, and 0.011, when using strategy A, B, C, or D (P<0.001, for comparison between the strategies), leading to at least one alert in 87.5%, 39.3%, 13.5%, or 7.81 % of the regimens. Similar average numbers of alerts were observed for medication regimens entered for written prescriptions.
The prescription of potentially hazardous drugs is common in patients with renal impairment. Alerting strategies including patient and drug-specific information to generate more specific alerts have the potential to reduce the alert burden by more than 90 %.
电子警报常常被医生忽视，部分原因是决策支持系统产生大量非特异性警报。本研究的目的是分析一所大学附属医院肾内科的关键药物处方，并评估不同警报策略对警报负担的影响。
在一项前瞻性观察研究中，当录入出院小结、门诊病历及书面处方的用药方案时，应用两种先进的自动生成警报的策略，并与两种基本参考策略进行比较。策略A在有药物特异性信息时生成警报，而策略B仅在患者的估计肾小球滤过率低于药物特异性值时生成警报。策略C和D纳入了更多患者特征和药物特异性信息以生成更具特异性的警报。
总体而言，观察期内共录入1012条用药方案。当使用策略A、B、C或D时，录入病历的用药方案中每种药物制剂的平均警报数分别为0.28、0.080、0.019和0.011（各策略间比较，P<0.001），导致至少一条警报的方案比例分别为87.5%、39.3%、13.5%或7.81%。书面处方录入的用药方案也观察到类似的平均警报数。
肾功能损害患者中开具潜在危险药物的情况很常见。纳入患者和药物特异性信息以生成更具特异性警报的策略有可能将警报负担降低90%以上。
