Azaz-Livshits T, Levy M, Sadan B, Shalit M, Geisslinger G, Brune K
Division of Medicine, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.
Br J Clin Pharmacol. 1998 Mar;45(3):309-14. doi: 10.1046/j.1365-2125.1998.00685.x.
To develop and assess the use of computerized laboratory data as a detection support tool of adverse drug reactions (ADRs) in hospital.
This was a retrospective observational study of 153 sequential medical admissions during a 2-month period to the 34-bed medical ward at the Hadassah University Hospital, Jerusalem, Israel. Measurements made were 1) Retrospective chart review for recognized and unrecognized adverse drug reactions (ADRs) and 2) Analysis of computerizied laboratory data according to defined automatic laboratory signals (ALS) for adverse reactions.
Forty ADRs have been detected in 38 out of the 153 hospital admissions (24.8%). Nine reactions were considered severe. Altogether 212 ALS were generated involving 86 admissions. In 25 (65.8%) of the ADR-positive admissions ADRs were detected through automatic signals generated from the laboratory data. ALS were detected in 56 out of the 115 (48.7%) ADR-negative admissions. Twenty-four (60%) of the ADRs were not recognized as such by the attending physicians. Two of these reactions were severe. ALS could have generated an alert for 19 (79.2%) of the unrecognized reactions.
Application of automatic laboratory signals can increase the rate of recognition of the ADRs and thereby improve medical care. The sensitivity and specificity of the method might be increased by refinement and redefinition of the signals.
开发并评估将计算机化实验室数据用作医院药物不良反应(ADR)检测支持工具的情况。
这是一项回顾性观察研究,对以色列耶路撒冷哈达萨大学医院拥有34张床位的内科病房在2个月期间连续收治的153例内科患者进行研究。所做的测量包括:1)对已识别和未识别的药物不良反应(ADR)进行回顾性病历审查;2)根据定义的不良反应自动实验室信号(ALS)分析计算机化实验室数据。
在153例住院患者中的38例(24.8%)检测到40例ADR。其中9例反应被认为是严重的。共产生212个ALS,涉及86例住院患者。在25例(65.8%)ADR阳性的住院患者中,通过实验室数据生成的自动信号检测到ADR。在115例(48.7%)ADR阴性的住院患者中,有56例检测到ALS。24例(60%)ADR未被主治医生识别。其中2例反应是严重的。ALS本可以对19例(79.2%)未被识别的反应发出警报。
应用自动实验室信号可以提高ADR的识别率,从而改善医疗护理。通过对信号进行细化和重新定义,可能会提高该方法的敏感性和特异性。