Risk analysis and assessment based on Sigma metrics and intended use
In order to ensure the quality in clinical laboratories and meet the low risk requirements of patients and clinicians, a risk analysis and assessment model based on Sigma metrics and intended use was constructed, based on which differential sigma performance ( ) expectations of 42 analytes were deve...
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Veröffentlicht in: | Biochemia Medica 2018-06, Vol.28 (2), p.020707-020707 |
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creator | Xia, Yong Xue, Hao Yan, Cunliang Li, Bowen Zhang, ShuQiong Li, Mingyang Ji, Ling |
description | In order to ensure the quality in clinical laboratories and meet the low risk requirements of patients and clinicians, a risk analysis and assessment model based on Sigma metrics and intended use was constructed, based on which differential sigma performance (
) expectations of 42 analytes were developed.
Failure mode and effects analysis was applied to produce an analytic risk rating based on three factors, each test of which was graded as follows: 1) Sigma metrics; 2) the severity of harm; 3) intended use. By multiplying the score of Sigma metrics by the score of severity of harm by the score of intended use, each was assigned a typical risk priority number (RPN), with RPN ≤ 25 rated as low risk. Low risk was defined as acceptable standards; the sigma performance expectations were calculated.
Among the 42 analytes, tests with
≥ 6, 5 ≤
< 6, 4 ≤
< 5, 3 ≤
< 4,
< 3 were 21, 5, 5, 6, and 5, respectively; there were 7 high-risk tests, 8 of them medium risk tests. According to the risk assessment conclusion, 13 tests had sigma performance expectations ≥ 6; 15 test items had sigma performance expectations ≥ 5, while 3 test items had sigma performance expectations ≥ 4; 11 test items had sigma performance expectations ≥ 3.
Constructing the risk analysis and assessment model based on Sigma metrics and intended use will help clinical laboratories to identify the high-risk tests more objectively and comprehensively. Such model can also be used to establish the sigma performance expectations and meet the low risk requirements of patients and clinicians. |
doi_str_mv | 10.11613/BM.2018.020707 |
format | Article |
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) expectations of 42 analytes were developed.
Failure mode and effects analysis was applied to produce an analytic risk rating based on three factors, each test of which was graded as follows: 1) Sigma metrics; 2) the severity of harm; 3) intended use. By multiplying the score of Sigma metrics by the score of severity of harm by the score of intended use, each was assigned a typical risk priority number (RPN), with RPN ≤ 25 rated as low risk. Low risk was defined as acceptable standards; the sigma performance expectations were calculated.
Among the 42 analytes, tests with
≥ 6, 5 ≤
< 6, 4 ≤
< 5, 3 ≤
< 4,
< 3 were 21, 5, 5, 6, and 5, respectively; there were 7 high-risk tests, 8 of them medium risk tests. According to the risk assessment conclusion, 13 tests had sigma performance expectations ≥ 6; 15 test items had sigma performance expectations ≥ 5, while 3 test items had sigma performance expectations ≥ 4; 11 test items had sigma performance expectations ≥ 3.
Constructing the risk analysis and assessment model based on Sigma metrics and intended use will help clinical laboratories to identify the high-risk tests more objectively and comprehensively. Such model can also be used to establish the sigma performance expectations and meet the low risk requirements of patients and clinicians.</description><identifier>ISSN: 1330-0962</identifier><identifier>EISSN: 1846-7482</identifier><identifier>DOI: 10.11613/BM.2018.020707</identifier><identifier>PMID: 30022882</identifier><language>eng</language><publisher>Croatia: Medicinska naklada</publisher><subject>Clinical Decision-Making ; failure mode and effects analysis ; Humans ; Original Papers ; risk analysis ; risk assessment ; Risk Assessment - methods ; Sigma metrics ; Six Sigma ; Total Quality Management - methods</subject><ispartof>Biochemia Medica, 2018-06, Vol.28 (2), p.020707-020707</ispartof><rights>Croatian Society of Medical Biochemistry and Laboratory Medicine. 2017 Croatian Society of Medical Biochemistry</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-3706c4eb0647d0d943414ce725e46a3e562b14526e874c9a1da09cd6819ed5bd3</citedby><cites>FETCH-LOGICAL-c431t-3706c4eb0647d0d943414ce725e46a3e562b14526e874c9a1da09cd6819ed5bd3</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/PMC6039164/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039164/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30022882$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xia, Yong</creatorcontrib><creatorcontrib>Xue, Hao</creatorcontrib><creatorcontrib>Yan, Cunliang</creatorcontrib><creatorcontrib>Li, Bowen</creatorcontrib><creatorcontrib>Zhang, ShuQiong</creatorcontrib><creatorcontrib>Li, Mingyang</creatorcontrib><creatorcontrib>Ji, Ling</creatorcontrib><title>Risk analysis and assessment based on Sigma metrics and intended use</title><title>Biochemia Medica</title><addtitle>Biochem Med (Zagreb)</addtitle><description>In order to ensure the quality in clinical laboratories and meet the low risk requirements of patients and clinicians, a risk analysis and assessment model based on Sigma metrics and intended use was constructed, based on which differential sigma performance (
) expectations of 42 analytes were developed.
Failure mode and effects analysis was applied to produce an analytic risk rating based on three factors, each test of which was graded as follows: 1) Sigma metrics; 2) the severity of harm; 3) intended use. By multiplying the score of Sigma metrics by the score of severity of harm by the score of intended use, each was assigned a typical risk priority number (RPN), with RPN ≤ 25 rated as low risk. Low risk was defined as acceptable standards; the sigma performance expectations were calculated.
Among the 42 analytes, tests with
≥ 6, 5 ≤
< 6, 4 ≤
< 5, 3 ≤
< 4,
< 3 were 21, 5, 5, 6, and 5, respectively; there were 7 high-risk tests, 8 of them medium risk tests. According to the risk assessment conclusion, 13 tests had sigma performance expectations ≥ 6; 15 test items had sigma performance expectations ≥ 5, while 3 test items had sigma performance expectations ≥ 4; 11 test items had sigma performance expectations ≥ 3.
Constructing the risk analysis and assessment model based on Sigma metrics and intended use will help clinical laboratories to identify the high-risk tests more objectively and comprehensively. Such model can also be used to establish the sigma performance expectations and meet the low risk requirements of patients and clinicians.</description><subject>Clinical Decision-Making</subject><subject>failure mode and effects analysis</subject><subject>Humans</subject><subject>Original Papers</subject><subject>risk analysis</subject><subject>risk assessment</subject><subject>Risk Assessment - methods</subject><subject>Sigma metrics</subject><subject>Six Sigma</subject><subject>Total Quality Management - methods</subject><issn>1330-0962</issn><issn>1846-7482</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVkUtP3TAQhS1UxHvdXZVlN7mMH7GdDVKB0lYCIUFZW449gCEP6smtxL-vaSgqKx95vjn2zGHsI4cV55rLw-OLlQBuVyDAgNlgO9wqXRtlxYeipYQaWi222S7RA0DTNNZssW0JIIS1YoedXiV6rPzo-2dKVESsPBESDTjOVecJYzWN1XW6G3w14JxTWKg0zjjGUl0T7rPNW98THryee-zm7OvPk-_1-eW3HydfzuugJJ9raUAHhR1oZSLEVknFVUAjGlTaS2y06LhqhEZrVGg9jx7aELXlLcami3KPHS2-T-tuwBjKF7Pv3VNOg8_PbvLJva-M6d7dTb-dBtlyrYpBvRjc5-Af3zUuN5QDFunKThthCv_59cE8_VojzW5IFLDv_YjTmgpmBLdWgS3o4YKGPBFlvH1z5-D-ZuWOL158rVuyKh2f_p_mjf8XjvwDcgaPZw</recordid><startdate>20180615</startdate><enddate>20180615</enddate><creator>Xia, Yong</creator><creator>Xue, Hao</creator><creator>Yan, Cunliang</creator><creator>Li, Bowen</creator><creator>Zhang, ShuQiong</creator><creator>Li, Mingyang</creator><creator>Ji, Ling</creator><general>Medicinska naklada</general><general>Croatian Society of Medical Biochemistry and Laboratory Medicine</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>VP8</scope><scope>5PM</scope></search><sort><creationdate>20180615</creationdate><title>Risk analysis and assessment based on Sigma metrics and intended use</title><author>Xia, Yong ; Xue, Hao ; Yan, Cunliang ; Li, Bowen ; Zhang, ShuQiong ; Li, Mingyang ; Ji, Ling</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-3706c4eb0647d0d943414ce725e46a3e562b14526e874c9a1da09cd6819ed5bd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Clinical Decision-Making</topic><topic>failure mode and effects analysis</topic><topic>Humans</topic><topic>Original Papers</topic><topic>risk analysis</topic><topic>risk assessment</topic><topic>Risk Assessment - methods</topic><topic>Sigma metrics</topic><topic>Six Sigma</topic><topic>Total Quality Management - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xia, Yong</creatorcontrib><creatorcontrib>Xue, Hao</creatorcontrib><creatorcontrib>Yan, Cunliang</creatorcontrib><creatorcontrib>Li, Bowen</creatorcontrib><creatorcontrib>Zhang, ShuQiong</creatorcontrib><creatorcontrib>Li, Mingyang</creatorcontrib><creatorcontrib>Ji, Ling</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>Hrcak: Portal of scientific journals of Croatia</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Biochemia Medica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xia, Yong</au><au>Xue, Hao</au><au>Yan, Cunliang</au><au>Li, Bowen</au><au>Zhang, ShuQiong</au><au>Li, Mingyang</au><au>Ji, Ling</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Risk analysis and assessment based on Sigma metrics and intended use</atitle><jtitle>Biochemia Medica</jtitle><addtitle>Biochem Med (Zagreb)</addtitle><date>2018-06-15</date><risdate>2018</risdate><volume>28</volume><issue>2</issue><spage>020707</spage><epage>020707</epage><pages>020707-020707</pages><issn>1330-0962</issn><eissn>1846-7482</eissn><abstract>In order to ensure the quality in clinical laboratories and meet the low risk requirements of patients and clinicians, a risk analysis and assessment model based on Sigma metrics and intended use was constructed, based on which differential sigma performance (
) expectations of 42 analytes were developed.
Failure mode and effects analysis was applied to produce an analytic risk rating based on three factors, each test of which was graded as follows: 1) Sigma metrics; 2) the severity of harm; 3) intended use. By multiplying the score of Sigma metrics by the score of severity of harm by the score of intended use, each was assigned a typical risk priority number (RPN), with RPN ≤ 25 rated as low risk. Low risk was defined as acceptable standards; the sigma performance expectations were calculated.
Among the 42 analytes, tests with
≥ 6, 5 ≤
< 6, 4 ≤
< 5, 3 ≤
< 4,
< 3 were 21, 5, 5, 6, and 5, respectively; there were 7 high-risk tests, 8 of them medium risk tests. According to the risk assessment conclusion, 13 tests had sigma performance expectations ≥ 6; 15 test items had sigma performance expectations ≥ 5, while 3 test items had sigma performance expectations ≥ 4; 11 test items had sigma performance expectations ≥ 3.
Constructing the risk analysis and assessment model based on Sigma metrics and intended use will help clinical laboratories to identify the high-risk tests more objectively and comprehensively. Such model can also be used to establish the sigma performance expectations and meet the low risk requirements of patients and clinicians.</abstract><cop>Croatia</cop><pub>Medicinska naklada</pub><pmid>30022882</pmid><doi>10.11613/BM.2018.020707</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Clinical Decision-Making failure mode and effects analysis Humans Original Papers risk analysis risk assessment Risk Assessment - methods Sigma metrics Six Sigma Total Quality Management - methods |
title | Risk analysis and assessment based on Sigma metrics and intended use |
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