Hui Qi Low, Hyun-Ki Kim, Sollip Kim, Tony Badrick, Tze Ping Loh, Chun Yee Lim
{"title":"基于患者的质量控制分析与评估(SPAE)电子表格。","authors":"Hui Qi Low, Hyun-Ki Kim, Sollip Kim, Tony Badrick, Tze Ping Loh, Chun Yee Lim","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Patient-based quality control (PBQC) is an alternate quality control technique to conventional (internal) quality control. It uses patient results generated for clinical care to monitor the analytical performance through statistical analysis. The use of PBQC in routine laboratory is impeded by lack of familiarity and appropriate informatics tool.</p><p><strong>Method: </strong>A Spreadsheet for PBQC Analysis and Evaluation (SPAE, based on Microsoft Excel) is developed. It incorporates IFCC recommended features for PBQC informatics tool that has been automated, including data visualization, data (Box-Cox) transformation, extreme value treatment (winsorization) and user parameter selection (block size, acceptable false positive rate, desirable bias for detection).</p><p><strong>Results: </strong>Following parameter selection and data input, the spreadsheet automatically calculates the winsorization limits, transformed values, performance verification metrics such as false positive rates and number of results affected before error detection (NPed) - a performance metric for how sensitive the PBQC model detects the predefined error (bias). The verified PBQC model can be used for routine monitoring. The performance of the spreadsheet tool was verified against an independent model based on Python. Laboratory users can download the tool at https://github.com/HuiQi96/PBQC/blob/main/PBQC_model_v2.2.zip.</p><p><strong>Discussion: </strong>The SPAE is a simple-to-use desktop tool that lowers the barrier for laboratory users to adopt PBQC in their quality control system. In addition, the spreadsheet can be used as an educational tool, such as when conducting a workshop, to help laboratory users better familiarize themselves with the PBQC concepts and used for independent verification of the output of another informatics tool.</p>","PeriodicalId":37192,"journal":{"name":"Electronic Journal of the International Federation of Clinical Chemistry and Laboratory Medicine","volume":"36 1","pages":"26-36"},"PeriodicalIF":0.0000,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11886628/pdf/","citationCount":"0","resultStr":"{\"title\":\"Spreadsheet for Patient-Based Quality Control Analysis and Evaluation (SPAE).\",\"authors\":\"Hui Qi Low, Hyun-Ki Kim, Sollip Kim, Tony Badrick, Tze Ping Loh, Chun Yee Lim\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Patient-based quality control (PBQC) is an alternate quality control technique to conventional (internal) quality control. It uses patient results generated for clinical care to monitor the analytical performance through statistical analysis. The use of PBQC in routine laboratory is impeded by lack of familiarity and appropriate informatics tool.</p><p><strong>Method: </strong>A Spreadsheet for PBQC Analysis and Evaluation (SPAE, based on Microsoft Excel) is developed. It incorporates IFCC recommended features for PBQC informatics tool that has been automated, including data visualization, data (Box-Cox) transformation, extreme value treatment (winsorization) and user parameter selection (block size, acceptable false positive rate, desirable bias for detection).</p><p><strong>Results: </strong>Following parameter selection and data input, the spreadsheet automatically calculates the winsorization limits, transformed values, performance verification metrics such as false positive rates and number of results affected before error detection (NPed) - a performance metric for how sensitive the PBQC model detects the predefined error (bias). The verified PBQC model can be used for routine monitoring. The performance of the spreadsheet tool was verified against an independent model based on Python. Laboratory users can download the tool at https://github.com/HuiQi96/PBQC/blob/main/PBQC_model_v2.2.zip.</p><p><strong>Discussion: </strong>The SPAE is a simple-to-use desktop tool that lowers the barrier for laboratory users to adopt PBQC in their quality control system. In addition, the spreadsheet can be used as an educational tool, such as when conducting a workshop, to help laboratory users better familiarize themselves with the PBQC concepts and used for independent verification of the output of another informatics tool.</p>\",\"PeriodicalId\":37192,\"journal\":{\"name\":\"Electronic Journal of the International Federation of Clinical Chemistry and Laboratory Medicine\",\"volume\":\"36 1\",\"pages\":\"26-36\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11886628/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronic Journal of the International Federation of Clinical Chemistry and Laboratory Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/3/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Journal of the International Federation of Clinical Chemistry and Laboratory Medicine","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
Spreadsheet for Patient-Based Quality Control Analysis and Evaluation (SPAE).
Introduction: Patient-based quality control (PBQC) is an alternate quality control technique to conventional (internal) quality control. It uses patient results generated for clinical care to monitor the analytical performance through statistical analysis. The use of PBQC in routine laboratory is impeded by lack of familiarity and appropriate informatics tool.
Method: A Spreadsheet for PBQC Analysis and Evaluation (SPAE, based on Microsoft Excel) is developed. It incorporates IFCC recommended features for PBQC informatics tool that has been automated, including data visualization, data (Box-Cox) transformation, extreme value treatment (winsorization) and user parameter selection (block size, acceptable false positive rate, desirable bias for detection).
Results: Following parameter selection and data input, the spreadsheet automatically calculates the winsorization limits, transformed values, performance verification metrics such as false positive rates and number of results affected before error detection (NPed) - a performance metric for how sensitive the PBQC model detects the predefined error (bias). The verified PBQC model can be used for routine monitoring. The performance of the spreadsheet tool was verified against an independent model based on Python. Laboratory users can download the tool at https://github.com/HuiQi96/PBQC/blob/main/PBQC_model_v2.2.zip.
Discussion: The SPAE is a simple-to-use desktop tool that lowers the barrier for laboratory users to adopt PBQC in their quality control system. In addition, the spreadsheet can be used as an educational tool, such as when conducting a workshop, to help laboratory users better familiarize themselves with the PBQC concepts and used for independent verification of the output of another informatics tool.