Van Hoof Viviane, Bench Suzanne, Soto Antonio Buño, Luppa Peter P, Malpass Anthony, Schilling Ulf Martin, Rooney Kevin D, Stretton Adam, Tintu Andrei N
Faculty of Medicine and Health Sciences, University of Antwerp, Wilrijk, Belgium.
Guys and St Thomas NHS Foundation Trust, London, UK.
Clin Chem Lab Med. 2022 May 24;60(8):1186-1201. doi: 10.1515/cclm-2022-0319. Print 2022 Jul 26.
Proposal of a risk analysis model to diminish negative impact on patient care by preanalytical errors in blood gas analysis (BGA).
Here we designed a Failure Mode and Effects Analysis (FMEA) risk assessment template for BGA, based on literature references and expertise of an international team of laboratory and clinical health care professionals.
The FMEA identifies pre-analytical process steps, errors that may occur whilst performing BGA (potential failure mode), possible consequences (potential failure effect) and preventive/corrective actions (current controls). Probability of failure occurrence (OCC), severity of failure (SEV) and probability of failure detection (DET) are scored per potential failure mode. OCC and DET depend on test setting and patient population e.g., they differ in primary community health centres as compared to secondary community hospitals and third line university or specialized hospitals. OCC and DET also differ between stand-alone and networked instruments, manual and automated patient identification, and whether results are automatically transmitted to the patient's electronic health record. The risk priority number (RPN = SEV × OCC × DET) can be applied to determine the sequence in which risks are addressed. RPN can be recalculated after implementing changes to decrease OCC and/or increase DET. Key performance indicators are also proposed to evaluate changes.
This FMEA model will help health care professionals manage and minimize the risk of preanalytical errors in BGA.
提出一种风险分析模型，以减少血气分析（BGA）中的分析前误差对患者护理的负面影响。
在此，我们基于文献参考以及国际实验室和临床医疗专业团队的专业知识，设计了一个用于BGA的失效模式与效应分析（FMEA）风险评估模板。
FMEA识别分析前的流程步骤、进行BGA时可能出现的误差（潜在失效模式）、可能的后果（潜在失效效应）以及预防/纠正措施（当前控制措施）。针对每个潜在失效模式对失效发生概率（OCC）、失效严重程度（SEV）和失效检测概率（DET）进行评分。OCC和DET取决于检测设置和患者群体，例如，与二级社区医院以及三级大学或专科医院相比，它们在初级社区卫生中心有所不同。OCC和DET在独立仪器与联网仪器、手动与自动患者识别以及结果是否自动传输到患者电子健康记录之间也存在差异。风险优先数（RPN = SEV×OCC×DET）可用于确定处理风险的顺序。在实施旨在降低OCC和/或提高DET的变更后，可以重新计算RPN值。还提出了关键绩效指标来评估变更情况。
该FMEA模型将有助于医疗专业人员管理并最小化BGA中分析前误差的风险。
