Sathe Laila M, Khan Nishrat N, Williams Jazmine M, Saul Rosita, Jajieh Kane, Sartippour Maryam R, Young Rachel, Xie Joanna, Marquette Dawn M, Duncan Tiffany, Eskin Eleazar, Arboleda Valerie A
Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, US.
UCLA SwabSeq COVID19 Laboratory, David Geffen School of Medicine at UCLA, Los Angeles, CA, US.
Lab Med. 2023 Sep 5;54(5):512-518. doi: 10.1093/labmed/lmac161.
Massive-scale SARS-CoV-2 testing using the SwabSeq diagnostic platform came with quality assurance challenges due to the novelty and scale of sequencing-based testing. The SwabSeq platform relies on accurate mapping between specimen identifiers and molecular barcodes to match a result back to a patient specimen. To identify and mitigate mapping errors, we instituted quality control using placement of negative controls within a rack of patient samples. We designed 2-dimensional paper templates to fit over a 96-position rack of specimens with holes to show the control tube placements. We designed and 3-dimensionally printed plastic templates that fit onto 4 racks of patient specimens and provide accurate indications of the correct control tube placements. The final plastic templates dramatically reduced plate mapping errors from 22.55% in January 2021 to less than 1% after implementation and training in January 2021. We show how 3D printing can be a cost-effective quality assurance tool to mitigate human error in the clinical laboratory.
由于基于测序的检测方法新颖且规模庞大，使用SwabSeq诊断平台进行大规模的严重急性呼吸综合征冠状病毒2（SARS-CoV-2）检测面临质量保证方面的挑战。SwabSeq平台依靠样本标识符与分子条形码之间的精确匹配，将检测结果与患者样本进行对应。为了识别并减少匹配错误，我们通过在患者样本架中放置阴性对照来进行质量控制。我们设计了二维纸质模板，可覆盖96孔的样本架，上面有孔以显示对照管的放置位置。我们还设计并3D打印了塑料模板，该模板可适配4个患者样本架，并能准确指示对照管的正确放置位置。最终使用的塑料模板显著减少了样本架匹配错误，从2021年1月的22.55%降至2021年1月实施并培训后不到1%。我们展示了3D打印如何成为一种具有成本效益的质量保证工具，以减少临床实验室中的人为错误。
