Classen D C, Pestotnik S L, Evans R S, Burke J P
Department of Clinical Epidemiology, LDS Hospital, Salt Lake City, UT 84143.
JAMA. 1991 Nov 27;266(20):2847-51.
To develop a new method to improve the detection and characterization of adverse drug events (ADEs) in hospital patients.
Prospective study of all patients admitted to our hospital over an 18-month period.
LDS Hospital, Salt Lake City, Utah, a 520-bed tertiary care center affiliated with the University of Utah School of Medicine, Salt Lake City.
We developed a computerized ADE monitor, and computer programs were written using an integrated hospital information system to allow for multiple source detection of potential ADEs occurring in hospital patients. Signals of potential ADEs, both voluntary and automated, included sudden medication stop orders, antidote ordering, and certain abnormal laboratory values. Each day, a list of all potential ADEs from these sources was generated, and a pharmacist reviewed the medical records of all patients with possible ADEs for accuracy and causality. Verified ADEs were characterized as mild, moderate, or severe and as type A (dose-dependent or predictable) or type B (idiosyncratic or allergic) reactions, and causality was further measured using a standardized scoring method.
The number and characterization of ADEs detected.
Over 18 months, we monitored 36,653 hospitalized patients. There were 731 verified ADEs identified in 648 patients, 701 ADEs were characterized as moderate or severe, and 664 were classified as type A reactions. During this same period, only nine ADEs were identified using traditional detection methods. Physicians, pharmacists, and nurses voluntarily reported 92 of the 731 ADEs detected using this automated system. The other 631 ADEs were detected from automated signals, the most common of which were diphenhydramine hydrochloride and naloxone hydrochloride use, high serum drug levels, leukopenia, and the use of phytonadione and antidiarrheals. The most common symptoms and signs were pruritus, nausea and/or vomiting, rash, and confusion-lethargy. The most common drug classes involved were analgesics, anti-infectives, and cardiovascular agents.
We believe that screening for ADEs with a computerized hospital information system offers a potential method for improving the detection and characterization of these events in hospital patients.
开发一种新方法,以改善对医院患者药物不良事件(ADEs)的检测与特征描述。
对我院18个月期间收治的所有患者进行前瞻性研究。
位于犹他州盐湖城的LDS医院,是一家拥有520张床位的三级护理中心,隶属于盐湖城犹他大学医学院。
我们开发了一个计算机化的ADE监测器,并利用综合医院信息系统编写计算机程序,以便对医院患者中发生的潜在ADEs进行多源检测。潜在ADEs的信号,包括主动和自动信号,有突然停药医嘱、解毒剂医嘱以及某些异常实验室值。每天都会生成一份来自这些来源的所有潜在ADEs清单,药剂师会查阅所有可能发生ADEs患者的病历,以核实准确性和因果关系。经核实的ADEs被分为轻度、中度或重度,以及A型(剂量依赖性或可预测性)或B型(特异质性或过敏性)反应,并使用标准化评分方法进一步衡量因果关系。
检测到的ADEs的数量和特征描述。
在18个月期间,我们监测了36653名住院患者。在648名患者中识别出731例经核实的ADEs,701例ADEs被判定为中度或重度,664例被归类为A型反应。在同一时期,使用传统检测方法仅识别出9例ADEs。医生、药剂师和护士主动报告了使用该自动系统检测到的731例ADEs中的92例。其他631例ADEs是从自动信号中检测到的,其中最常见的是使用盐酸苯海拉明和盐酸纳洛酮、血清药物水平过高、白细胞减少以及使用维生素K和止泻药。最常见的症状和体征是瘙痒、恶心和/或呕吐、皮疹以及意识模糊-嗜睡。涉及的最常见药物类别是镇痛药、抗感染药和心血管药物。
我们认为,利用计算机化医院信息系统筛查ADEs为改善对医院患者中这些事件的检测与特征描述提供了一种潜在方法。