Six Sigma Metrics: An Evolving Indicator of Quality Assurance for Clinical Biochemistry
Introduction: The analytical phase of the total testing process is the one in which the clinical biochemist can directly intervene to improve the quality of tests reporting. The sigma metrics and Operational Process Specification (OPSpec) chart can specify to which category the laboratory belongs....
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| Format: | Article |
| Language: | English |
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JCDR Research and Publications Private Limited
2022-08-01
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| Series: | Journal of Clinical and Diagnostic Research |
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| Online Access: | https://www.jcdr.net/articles/PDF/16718/56691_CE_(PRI)_F(KR)_PF1(AG_SS)_PFA(AG_KM)_PN(KM).pdf |
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| author | Devi Prasad Pradhan Debasish Pandit Sibasish Sahoo Roma Rattan Sucharita Mohanty |
| author_facet | Devi Prasad Pradhan Debasish Pandit Sibasish Sahoo Roma Rattan Sucharita Mohanty |
| author_sort | Devi Prasad Pradhan |
| collection | DOAJ |
| description | Introduction: The analytical phase of the total testing process is the one in which the clinical biochemist can directly intervene to improve the quality of tests reporting. The sigma metrics and Operational Process Specification (OPSpec) chart can specify to which category the laboratory belongs.
Aim: To apply sigma metrics to analytical process of testing, do the root cause analysis and apply the corrective measures according to Westgard rules to improve laboratory performance towards the quality assurances.
Materials and Methods: This was a retrospective-prospective study carried out in a clinical laboratory of MKCG Medical College and Hospital, Berhampur, Odisha, India, from July 2020 to March 2021. A retrospective secondary data analysis of six months duration was carried out in a clinical chemistry laboratory with a follow-up prospective study for three months. During this period, 16 analytes were tabulated to analyse the Internal Quality Control (IQC). External Quality Control (EQC) for the same analytes were obtained on monthly basis and the sigma metrics was calculated for each analytes. For analytes with sigma value <3, appropriate measures were taken according to Westgard rules to improvise the quality of laboratory investigations. The statistical analysis of sigma metrics was performed in “R” v-3.6.3.
Results: Out of total 16 analytes, three analytes at level 1 and two analytes at level 2 Quality control (QC) showed a world class performance whereas four analytes showed a poor performance at both the QC levels with sigma metrics value <3. From Quality Goal Index (QGI) and root cause analysis, the source of error was detected and corrected.
Conclusion: The inaccuracy and imprecision of different parameters in the analytical phase of the testing process can be addressed by calculating the sigma metrics and do the root cause analysis. Application of corrective measures according to Westgard rule can improve the laboratory performance towards the quality assurance. |
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| format | Article |
| id | doaj.art-cbd1786545e74d11a4814a808f4d83ee |
| institution | Directory Open Access Journal |
| issn | 2249-782X 0973-709X |
| language | English |
| last_indexed | 2024-04-10T09:33:32Z |
| publishDate | 2022-08-01 |
| publisher | JCDR Research and Publications Private Limited |
| record_format | Article |
| series | Journal of Clinical and Diagnostic Research |
| spelling | doaj.art-cbd1786545e74d11a4814a808f4d83ee2023-02-18T07:00:03ZengJCDR Research and Publications Private LimitedJournal of Clinical and Diagnostic Research2249-782X0973-709X2022-08-01168BC14BC1810.7860/JCDR/2022/56691.16718Six Sigma Metrics: An Evolving Indicator of Quality Assurance for Clinical BiochemistryDevi Prasad Pradhan0Debasish Pandit1Sibasish Sahoo2Roma Rattan3Sucharita Mohanty4Assistant Professor, Department of Biochemistry, MKCG Medical College, Berhampur, Odisha, India.Tutor, Department of Community Medicine, SJMCH, Puri, Odisha, India.Assistant Professor, Department of Biochemistry, AIIMS, Kalyani, West Bengal, India.Professor, Department of Biochemistry, GMCH, Sundergarh, Odisha, India.Professor, Department of Biochemistry, BBMCH, Bolangir, Odisha, India.Introduction: The analytical phase of the total testing process is the one in which the clinical biochemist can directly intervene to improve the quality of tests reporting. The sigma metrics and Operational Process Specification (OPSpec) chart can specify to which category the laboratory belongs. Aim: To apply sigma metrics to analytical process of testing, do the root cause analysis and apply the corrective measures according to Westgard rules to improve laboratory performance towards the quality assurances. Materials and Methods: This was a retrospective-prospective study carried out in a clinical laboratory of MKCG Medical College and Hospital, Berhampur, Odisha, India, from July 2020 to March 2021. A retrospective secondary data analysis of six months duration was carried out in a clinical chemistry laboratory with a follow-up prospective study for three months. During this period, 16 analytes were tabulated to analyse the Internal Quality Control (IQC). External Quality Control (EQC) for the same analytes were obtained on monthly basis and the sigma metrics was calculated for each analytes. For analytes with sigma value <3, appropriate measures were taken according to Westgard rules to improvise the quality of laboratory investigations. The statistical analysis of sigma metrics was performed in “R” v-3.6.3. Results: Out of total 16 analytes, three analytes at level 1 and two analytes at level 2 Quality control (QC) showed a world class performance whereas four analytes showed a poor performance at both the QC levels with sigma metrics value <3. From Quality Goal Index (QGI) and root cause analysis, the source of error was detected and corrected. Conclusion: The inaccuracy and imprecision of different parameters in the analytical phase of the testing process can be addressed by calculating the sigma metrics and do the root cause analysis. Application of corrective measures according to Westgard rule can improve the laboratory performance towards the quality assurance.https://www.jcdr.net/articles/PDF/16718/56691_CE_(PRI)_F(KR)_PF1(AG_SS)_PFA(AG_KM)_PN(KM).pdfimprecisioninaccuracyquality goal indexquality controlroot cause analysis |
| spellingShingle | Devi Prasad Pradhan Debasish Pandit Sibasish Sahoo Roma Rattan Sucharita Mohanty Six Sigma Metrics: An Evolving Indicator of Quality Assurance for Clinical Biochemistry Journal of Clinical and Diagnostic Research imprecision inaccuracy quality goal index quality control root cause analysis |
| title | Six Sigma Metrics: An Evolving Indicator of Quality Assurance for Clinical Biochemistry |
| title_full | Six Sigma Metrics: An Evolving Indicator of Quality Assurance for Clinical Biochemistry |
| title_fullStr | Six Sigma Metrics: An Evolving Indicator of Quality Assurance for Clinical Biochemistry |
| title_full_unstemmed | Six Sigma Metrics: An Evolving Indicator of Quality Assurance for Clinical Biochemistry |
| title_short | Six Sigma Metrics: An Evolving Indicator of Quality Assurance for Clinical Biochemistry |
| title_sort | six sigma metrics an evolving indicator of quality assurance for clinical biochemistry |
| topic | imprecision inaccuracy quality goal index quality control root cause analysis |
| url | https://www.jcdr.net/articles/PDF/16718/56691_CE_(PRI)_F(KR)_PF1(AG_SS)_PFA(AG_KM)_PN(KM).pdf |
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