Kaplan H S, Battles J B, Van der Schaaf T W, Shea C E, Mercer S Q
Department of Pathology, University of Texas Southwestern Medical Center at Dallas, USA.
Transfusion. 1998 Nov-Dec;38(11-12):1071-81. doi: 10.1046/j.1537-2995.1998.38111299056319.x.
Transfusion medicine lacks a standard method for the systematic collection and analysis of event reports. Review of event reports from the Food and Drug Administration (FDA) showed a relative paucity of information on event causation. Thus, a causal analysis method was developed as part of a prototype Medical Event Reporting System for Transfusion Medicine (MERS-TM).
MERS-TM functions within existing quality assurance systems and utilizes descriptive coding and causal classification schemes. The descriptive classification system, based upon current FDA coding, was modified to meet participant needs. The Eindhoven Classification Model (Medical Version) was adopted for causal classification and analysis. Inter-rater reliability for the MERS-TM and among participating organizations was performed with the development group in the United States and with a safety science research group in the Netherlands. The MERS-TM was then tested with events reported by participants.
Data from 503 event reports from two blood centers and two transfusion services are discussed. The data showed multiple causes for events and more latent causes than previously recognized. The distribution of causes was remarkably similar to that in an industrial setting outside of medicine that uses the same classification approach. There was a high degree of inter-rater reliability when the same events were analyzed by quality assurance personnel in different participating organizations. These personnel found the method practical and useful for providing new insights into conditions producing undesired events.
A generally applicable and reliable method for identifying and quantifying problems that exist throughout transfusion medicine will be a valuable addition to event reporting activity. By using a common taxonomy, participants can compare their experience with that of others. If proven as readily implementable and useful as shown in initial studies, MERS-TM is a potential standard for transfusion medicine.
输血医学缺乏用于系统收集和分析事件报告的标准方法。对美国食品药品监督管理局（FDA）的事件报告进行审查发现，关于事件因果关系的信息相对较少。因此，作为输血医学医疗事件报告系统原型（MERS-TM）的一部分，开发了一种因果分析方法。
MERS-TM在现有的质量保证系统内运行，并采用描述性编码和因果分类方案。基于当前FDA编码的描述性分类系统进行了修改，以满足参与者的需求。因果分类和分析采用了埃因霍温分类模型（医学版）。在美国的开发团队和荷兰的一个安全科学研究团队中，对MERS-TM以及参与组织之间的评分者间信度进行了评估。然后，使用参与者报告的事件对MERS-TM进行了测试。
讨论了来自两个血液中心和两个输血服务机构的503份事件报告的数据。数据显示事件存在多种原因，潜在原因比之前认识到的更多。原因分布与采用相同分类方法的医学以外工业环境中的情况非常相似。当不同参与组织的质量保证人员对相同事件进行分析时，评分者间信度很高。这些人员发现该方法对于深入了解导致不良事件的情况切实有用。
一种普遍适用且可靠的方法，用于识别和量化输血医学中存在的问题，将是事件报告活动的一项宝贵补充。通过使用通用分类法，参与者可以将自己的经验与他人的经验进行比较。如果如初步研究所示，证明该方法易于实施且有用，那么MERS-TM有可能成为输血医学的标准。
