Selecting a Risk-Based SQC Procedure for a HbA1c Total QC Plan
Background: Recent US practice guidelines and laboratory regulations for quality control (QC) emphasize the development of QC plans and the application of risk management principles. The US Clinical Laboratory Improvement Amendments (CLIA) now includes an option to comply with QC regulations by deve...
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Veröffentlicht in: | Journal of diabetes science and technology 2018-07, Vol.12 (4), p.780-785 |
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creator | Westgard, Sten A. Bayat, Hassan Westgard, James O. |
description | Background:
Recent US practice guidelines and laboratory regulations for quality control (QC) emphasize the development of QC plans and the application of risk management principles. The US Clinical Laboratory Improvement Amendments (CLIA) now includes an option to comply with QC regulations by developing an individualized QC plan (IQCP) based on a risk assessment of the total testing process. The Clinical and Laboratory Standards Institute (CLSI) has provided new practice guidelines for application of risk management to QC plans and statistical QC (SQC).
Methods:
We describe an alternative approach for developing a total QC plan (TQCP) that includes a risk-based SQC procedure. CLIA compliance is maintained by analyzing at least 2 levels of controls per day. A Sigma-Metric SQC Run Size nomogram provides a graphical tool to simplify the selection of risk-based SQC procedures.
Applications:
Current HbA1c method performance, as demonstrated by published method validation studies, is estimated to be 4-Sigma quality at best. Optimal SQC strategies require more QC than the CLIA minimum requirement of 2 levels per day. More complex control algorithms, more control measurements, and a bracketed mode of operation are needed to assure the intended quality of results.
Conclusions:
A total QC plan with a risk-based SQC procedure provides a simpler alternative to an individualized QC plan. A Sigma-Metric SQC Run Size nomogram provides a practical tool for selecting appropriate control rules, numbers of control measurements, and run size (or frequency of SQC). Applications demonstrate the need for continued improvement of analytical performance of HbA1c laboratory methods. |
doi_str_mv | 10.1177/1932296817729488 |
format | Article |
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Recent US practice guidelines and laboratory regulations for quality control (QC) emphasize the development of QC plans and the application of risk management principles. The US Clinical Laboratory Improvement Amendments (CLIA) now includes an option to comply with QC regulations by developing an individualized QC plan (IQCP) based on a risk assessment of the total testing process. The Clinical and Laboratory Standards Institute (CLSI) has provided new practice guidelines for application of risk management to QC plans and statistical QC (SQC).
Methods:
We describe an alternative approach for developing a total QC plan (TQCP) that includes a risk-based SQC procedure. CLIA compliance is maintained by analyzing at least 2 levels of controls per day. A Sigma-Metric SQC Run Size nomogram provides a graphical tool to simplify the selection of risk-based SQC procedures.
Applications:
Current HbA1c method performance, as demonstrated by published method validation studies, is estimated to be 4-Sigma quality at best. Optimal SQC strategies require more QC than the CLIA minimum requirement of 2 levels per day. More complex control algorithms, more control measurements, and a bracketed mode of operation are needed to assure the intended quality of results.
Conclusions:
A total QC plan with a risk-based SQC procedure provides a simpler alternative to an individualized QC plan. A Sigma-Metric SQC Run Size nomogram provides a practical tool for selecting appropriate control rules, numbers of control measurements, and run size (or frequency of SQC). Applications demonstrate the need for continued improvement of analytical performance of HbA1c laboratory methods.</description><identifier>ISSN: 1932-2968</identifier><identifier>EISSN: 1932-2968</identifier><identifier>EISSN: 1932-3107</identifier><identifier>DOI: 10.1177/1932296817729488</identifier><identifier>PMID: 28905657</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Glycated Hemoglobin - analysis ; Humans ; Laboratories - standards ; Quality Control</subject><ispartof>Journal of diabetes science and technology, 2018-07, Vol.12 (4), p.780-785</ispartof><rights>2017 Diabetes Technology Society</rights><rights>2017 Diabetes Technology Society 2017 Diabetes Technology Society</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3498-ff50504ec9ccd982c32b1bc75664a045dff673dfc3147f9235d1bd910ef8c21a3</citedby><cites>FETCH-LOGICAL-c3498-ff50504ec9ccd982c32b1bc75664a045dff673dfc3147f9235d1bd910ef8c21a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6134308/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6134308/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,21799,27903,27904,43600,43601,53770,53772</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28905657$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Westgard, Sten A.</creatorcontrib><creatorcontrib>Bayat, Hassan</creatorcontrib><creatorcontrib>Westgard, James O.</creatorcontrib><title>Selecting a Risk-Based SQC Procedure for a HbA1c Total QC Plan</title><title>Journal of diabetes science and technology</title><addtitle>J Diabetes Sci Technol</addtitle><description>Background:
Recent US practice guidelines and laboratory regulations for quality control (QC) emphasize the development of QC plans and the application of risk management principles. The US Clinical Laboratory Improvement Amendments (CLIA) now includes an option to comply with QC regulations by developing an individualized QC plan (IQCP) based on a risk assessment of the total testing process. The Clinical and Laboratory Standards Institute (CLSI) has provided new practice guidelines for application of risk management to QC plans and statistical QC (SQC).
Methods:
We describe an alternative approach for developing a total QC plan (TQCP) that includes a risk-based SQC procedure. CLIA compliance is maintained by analyzing at least 2 levels of controls per day. A Sigma-Metric SQC Run Size nomogram provides a graphical tool to simplify the selection of risk-based SQC procedures.
Applications:
Current HbA1c method performance, as demonstrated by published method validation studies, is estimated to be 4-Sigma quality at best. Optimal SQC strategies require more QC than the CLIA minimum requirement of 2 levels per day. More complex control algorithms, more control measurements, and a bracketed mode of operation are needed to assure the intended quality of results.
Conclusions:
A total QC plan with a risk-based SQC procedure provides a simpler alternative to an individualized QC plan. A Sigma-Metric SQC Run Size nomogram provides a practical tool for selecting appropriate control rules, numbers of control measurements, and run size (or frequency of SQC). Applications demonstrate the need for continued improvement of analytical performance of HbA1c laboratory methods.</description><subject>Glycated Hemoglobin - analysis</subject><subject>Humans</subject><subject>Laboratories - standards</subject><subject>Quality Control</subject><issn>1932-2968</issn><issn>1932-2968</issn><issn>1932-3107</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kEtPwzAQhC0EoqVw54Ry5BLwI07sS6VSAUWqxKPlbDmOXVLSuNgJEv8eRy1VQeK0q53ZsfcD4BzBK4Sy7BpxgjFPWegxTxg7AP1uFHezw72-B068X0JIE5Zlx6CHGYc0pVkfDGe60qop60Uko5fSv8c30usimj2PoydnlS5apyNjXZAn-QipaG4bWUWdXMn6FBwZWXl9tq0D8Hp3Ox9P4unj_cN4NI0VSTiLjaGQwkQrrlTBGVYE5yhXGU3TRMKEFsakGSmMIijJDMeEFigvOILaMIWRJAMw3OSu23ylC6XrxslKrF25ku5LWFmK30pdvomF_RQpIgmBLARcbgOc_Wi1b8Sq9EpX4QZtWy8CKsYogryzwo1VOeu902b3DIKiwy7-Yg8rF_vf2y38cA6GeGPwcqHF0rauDrj-D_wG7dyIlQ</recordid><startdate>20180701</startdate><enddate>20180701</enddate><creator>Westgard, Sten A.</creator><creator>Bayat, Hassan</creator><creator>Westgard, James O.</creator><general>SAGE Publications</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20180701</creationdate><title>Selecting a Risk-Based SQC Procedure for a HbA1c Total QC Plan</title><author>Westgard, Sten A. ; Bayat, Hassan ; Westgard, James O.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3498-ff50504ec9ccd982c32b1bc75664a045dff673dfc3147f9235d1bd910ef8c21a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Glycated Hemoglobin - analysis</topic><topic>Humans</topic><topic>Laboratories - standards</topic><topic>Quality Control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Westgard, Sten A.</creatorcontrib><creatorcontrib>Bayat, Hassan</creatorcontrib><creatorcontrib>Westgard, James O.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of diabetes science and technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Westgard, Sten A.</au><au>Bayat, Hassan</au><au>Westgard, James O.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Selecting a Risk-Based SQC Procedure for a HbA1c Total QC Plan</atitle><jtitle>Journal of diabetes science and technology</jtitle><addtitle>J Diabetes Sci Technol</addtitle><date>2018-07-01</date><risdate>2018</risdate><volume>12</volume><issue>4</issue><spage>780</spage><epage>785</epage><pages>780-785</pages><issn>1932-2968</issn><eissn>1932-2968</eissn><eissn>1932-3107</eissn><abstract>Background:
Recent US practice guidelines and laboratory regulations for quality control (QC) emphasize the development of QC plans and the application of risk management principles. The US Clinical Laboratory Improvement Amendments (CLIA) now includes an option to comply with QC regulations by developing an individualized QC plan (IQCP) based on a risk assessment of the total testing process. The Clinical and Laboratory Standards Institute (CLSI) has provided new practice guidelines for application of risk management to QC plans and statistical QC (SQC).
Methods:
We describe an alternative approach for developing a total QC plan (TQCP) that includes a risk-based SQC procedure. CLIA compliance is maintained by analyzing at least 2 levels of controls per day. A Sigma-Metric SQC Run Size nomogram provides a graphical tool to simplify the selection of risk-based SQC procedures.
Applications:
Current HbA1c method performance, as demonstrated by published method validation studies, is estimated to be 4-Sigma quality at best. Optimal SQC strategies require more QC than the CLIA minimum requirement of 2 levels per day. More complex control algorithms, more control measurements, and a bracketed mode of operation are needed to assure the intended quality of results.
Conclusions:
A total QC plan with a risk-based SQC procedure provides a simpler alternative to an individualized QC plan. A Sigma-Metric SQC Run Size nomogram provides a practical tool for selecting appropriate control rules, numbers of control measurements, and run size (or frequency of SQC). Applications demonstrate the need for continued improvement of analytical performance of HbA1c laboratory methods.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><pmid>28905657</pmid><doi>10.1177/1932296817729488</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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source | PubMed (Medline); SAGE Publications; MEDLINE; EZB Electronic Journals Library |
subjects | Glycated Hemoglobin - analysis Humans Laboratories - standards Quality Control |
title | Selecting a Risk-Based SQC Procedure for a HbA1c Total QC Plan |
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