Department of Transfusion Medicine, SPS Hospitals, Ludhiana, India.
Department of Biochemistry, Dayanand Medical College and Hospital, Ludhiana, India.
Vox Sang. 2022 Nov;117(11):1271-1278. doi: 10.1111/vox.13349. Epub 2022 Sep 14.
Transfusion errors can occur anywhere from blood donation to final blood transfusion. They are a source of increased cost and patient mortality. Automated workflows can reduce transcription errors, but resource-poor centres still use semi-automated/manual method for testing including manual labelling of column agglutination cards/testing tubes. Missing out any details on these cards can lead to errors in reporting results, wastage and loss of resources and effort. The aim of this study was to implement Six Sigma DMAIC (Define, Measure, Analyse, Improve and Control) methodology to reduce transcription errors while labelling gel card in immunohaematology lab to zero defect.
In this prospective study, transcription errors while manually performing 200 tests with 1400 opportunities were analysed. Baseline variables like number of errors, defects per million opportunities and sigma level in our current setup were measured. With the application of DMAIC methodology, root cause analysis for each error using Ishikawa diagram and structured Interviews were done to identify causes. A multipronged approach to deal with errors was done to improve critical areas using brainstorming sessions and developing training sheets for practice. After implementing the changes, baseline variables were reanalysed.
Application of DMAIC resulted in an overall reduction in defects from 34.86% to 0.56% with sigma level improvement from 1.89 to 4.08.
Six Sigma methodology can be used in a resource-poor setting even with lack of automation to ensure error-free process flow.
从献血到最终输血,输血错误可能发生在任何环节。它们是增加成本和患者死亡率的一个来源。自动化工作流程可以减少转录错误,但资源匮乏的中心仍然使用半自动/手动方法进行测试,包括手动标记凝胶卡/测试管的柱凝集。如果在这些卡片上遗漏任何细节,可能会导致报告结果出错、浪费和资源以及努力的损失。本研究的目的是实施六西格玛 DMAIC(定义、测量、分析、改进和控制)方法,以减少免疫血液学实验室在标记凝胶卡时的转录错误,达到零缺陷。
在这项前瞻性研究中,分析了在手动进行 200 次测试、有 1400 次机会的情况下发生的转录错误。测量了当前设置中的错误数量、每百万机会缺陷数和西格玛水平等基线变量。通过应用 DMAIC 方法,使用石川图和结构化访谈对每个错误进行根本原因分析,以确定原因。通过头脑风暴会议和制定练习培训表,针对关键领域采取了多管齐下的方法来改进错误处理。在实施变更后,重新分析了基线变量。
DMAIC 的应用使缺陷总数从 34.86%降至 0.56%,西格玛水平从 1.89 提高到 4.08。
即使在缺乏自动化的情况下,六西格玛方法也可以在资源匮乏的环境中使用,以确保无错误的流程。