Plot3asic, three level QC data plotting and analysis freeware, for addressing cost of quality issues in diagnostic laboratories at resource constrained settings - Gupta, Rajarshi (Eastern Journal of Medical Sciences, 2019)
Objectives: In the rapidly evolving field of laboratory medicine, Quality Control (QC) is paramount in ensuring result accuracy and precision. However, QC procedures incur high cost of quality (COQ) which is often a hurdle to laboratories in resource constrained settings. Proprietary QC software is either expensive or tethered to proprietary platforms. Open source statistical libraries require considerable coding expertise often unavailable with laboratory personnel. Therefore, Plot3asic was developed as a freeware for generating publication quality QC plots with Westgard rule violation checks across three control levels. Methods: Plot3asic was developed using Python3 with ‘plotly’, an open source visualization toolbox. QC rules implemented by Plot3asic are adapted from Westgard rules. Mathematical calculations were independently verified by two investigators. Artificial datasets with known QC violations were analyzed using Plot3asic. Commercial QC material run data for the month of June 2019 were simultaneously analyzed on MultiXLv2017.01A(EM200) platform (Transasia/Erba Mannheim) and Plot3asic. Results: The results were generated as HTML files. The application was able to identify all QC violations as claimed. There was 100% corroboration between the violations flagged by MultiXLv2017.01A(EM200) platform and Plot3asic. The application also calculates sigma metric should the user choose to do so. Conclusion: To the best of our knowledge, Plot3asic provides features that no other freeware does till date. Determination of sigma metric helps streamline QC and reduce COQ. Plot3asic does not interface with proprietary platforms and is particularly helpful in semi-automated and manual assay data analysis in resource constrained settings.