Department of Clinical Laboratory, Hospital Universitario de San Juan, Alicante, Spain.
Scand J Clin Lab Invest. 2009;69(8):822-6. doi: 10.3109/00365510903288352.
The objectives of this research were to show the most frequent preanalytical sample errors from two distinct patient populations and blood-drawing personnel, to calculate preanalytical quality specifications, and to demonstrate an improvement strategy for patients whose samples have been drawn in the primary health care center by means of a monthly preanalytical quality control report based on statistical process control (SPC).
We collected preanalytical errors from the tests requested for hematology, coagulation, chemistry, and urine samples in both populations. To monitor an improvement strategy, we designed a set of indicators. The indicator results for 35 months were entered into the statistical software application, where they were statistically analyzed. The preanalytical quality specifications were calculated using the SPC control charts. The intervention consisted of the sending of a monthly preanalytical quality report to a pilot Decentralized Phlebotomy Center (DPC) and setting up a direct communication channel between the laboratory and the DPC.
Fewer errors were observed when the sample drawing was carried out by the laboratory personnel, showing distinct preanalytical quality specifications. Improvements were seen in the DPC after four months of the improvement strategy.
We show a practical and effective methodology for the identification, monitoring, and reduction of preanalytical errors using the technology employed in daily total testing laboratory process.
本研究旨在展示来自两个不同患者群体和采血人员的最常见的分析前样本错误，计算分析前质量规范，并展示一种改进策略，该策略针对在基层医疗中心采集的样本，每月基于统计过程控制 (SPC) 的分析前质量控制报告。
我们收集了两个群体的血液、凝血、化学和尿液样本的分析前错误。为了监测改进策略，我们设计了一套指标。35 个月的指标结果被输入到统计软件应用程序中进行统计分析。使用 SPC 控制图计算分析前质量规范。干预措施包括向试点分散采血中心 (DPC) 发送每月的分析前质量报告，并在实验室和 DPC 之间建立直接沟通渠道。
当由实验室人员进行样本采集时，观察到的错误较少，显示出明显的分析前质量规范。改进策略实施四个月后，在 DPC 中看到了改进。
我们展示了一种实用有效的方法，用于使用日常总测试实验室过程中使用的技术来识别、监测和减少分析前错误。
