Strategies to shorten turnaround time in outpatient laboratory
Background Turnaround time (TAT) is one of the most important indicators of laboratory quality. For the outpatient routine chemistry tests whose results are checked by clinicians on the same day, we set a quality goal that >90% of these samples should be reported within 60 min. As more than 20% o...
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| Veröffentlicht in: | Journal of clinical laboratory analysis 2022-10, Vol.36 (10), p.n/a |
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| description | Background
Turnaround time (TAT) is one of the most important indicators of laboratory quality. For the outpatient routine chemistry tests whose results are checked by clinicians on the same day, we set a quality goal that >90% of these samples should be reported within 60 min. As more than 20% of the samples failed to achieve this goal in 2020, we introduced an additional autoanalyzer and a real‐time monitoring system to improve this rate.
Methods
As the TAT of the pre‐analytical phase is the greatest contributor to TAT, we divided it into sampling, sample transport, and sample preparation times. An additional autoanalyzer was introduced, and its effect on TAT improvement was evaluated with the TAT data of June and July 2020. A real‐time monitoring system was introduced to sort delayed samples, and its effect was assessed with the TAT data of June and July 2021. TAT data from December 2019 to January 2020 were set as baseline controls.
Results
The preparation time comprised the largest proportion of TAT. Although there was a slight decrease in overall TAT after the introduction of the above two strategies, the target TAT achievement rate increased significantly from 78.5% to 88.7% (p |
| doi_str_mv | 10.1002/jcla.24665 |
| format | Article |
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Turnaround time (TAT) is one of the most important indicators of laboratory quality. For the outpatient routine chemistry tests whose results are checked by clinicians on the same day, we set a quality goal that >90% of these samples should be reported within 60 min. As more than 20% of the samples failed to achieve this goal in 2020, we introduced an additional autoanalyzer and a real‐time monitoring system to improve this rate.
Methods
As the TAT of the pre‐analytical phase is the greatest contributor to TAT, we divided it into sampling, sample transport, and sample preparation times. An additional autoanalyzer was introduced, and its effect on TAT improvement was evaluated with the TAT data of June and July 2020. A real‐time monitoring system was introduced to sort delayed samples, and its effect was assessed with the TAT data of June and July 2021. TAT data from December 2019 to January 2020 were set as baseline controls.
Results
The preparation time comprised the largest proportion of TAT. Although there was a slight decrease in overall TAT after the introduction of the above two strategies, the target TAT achievement rate increased significantly from 78.5% to 88.7% (p < 0.001).
Conclusions
We checked the cause of TAT prolongation and introduced new strategies to improve it. The addition of an autoanalyzer per se was not so effective but was better when combined with the real‐time monitoring system. Such strategies would increase the quality of the laboratory services.
To identify the delayed section, we further divided the pre‐analytical phase into three substeps. Among them, preparation time comprised the largest proportion of TAT. As the samples are rushed early in the morning, we devised a real‐time monitoring system to set the test priority of samples based on the time elapsed and assign them to four autoanalyzers considering their workload.</description><identifier>ISSN: 0887-8013</identifier><identifier>EISSN: 1098-2825</identifier><identifier>DOI: 10.1002/jcla.24665</identifier><language>eng</language><publisher>New York: John Wiley & Sons, Inc</publisher><subject>autoanalyzer ; Automation ; Bar codes ; Chi-square test ; Information systems ; Laboratories ; Monitoring systems ; outpatient testing ; Phlebotomy ; priority ; real‐time monitoring ; turnaround time ; Workloads</subject><ispartof>Journal of clinical laboratory analysis, 2022-10, Vol.36 (10), p.n/a</ispartof><rights>2022 The Authors. published by Wiley Periodicals LLC.</rights><rights>2022. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3375-9c08a6a237eead22bcbdb4933f954d71eb10756c83f420677b4fd23455b5f3a23</citedby><cites>FETCH-LOGICAL-c3375-9c08a6a237eead22bcbdb4933f954d71eb10756c83f420677b4fd23455b5f3a23</cites><orcidid>0000-0003-3956-6397 ; 0000-0002-5792-973X ; 0000-0002-5158-2130 ; 0000-0002-3271-9306 ; 0000-0002-9756-0295</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjcla.24665$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjcla.24665$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,864,1417,11562,27924,27925,45574,45575,46052,46476</link.rule.ids></links><search><creatorcontrib>Lee, Seunghoo</creatorcontrib><creatorcontrib>Yoon, Sangpil</creatorcontrib><creatorcontrib>Lee, Woochang</creatorcontrib><creatorcontrib>Chun, Sail</creatorcontrib><creatorcontrib>Min, Won‐Ki</creatorcontrib><title>Strategies to shorten turnaround time in outpatient laboratory</title><title>Journal of clinical laboratory analysis</title><description>Background
Turnaround time (TAT) is one of the most important indicators of laboratory quality. For the outpatient routine chemistry tests whose results are checked by clinicians on the same day, we set a quality goal that >90% of these samples should be reported within 60 min. As more than 20% of the samples failed to achieve this goal in 2020, we introduced an additional autoanalyzer and a real‐time monitoring system to improve this rate.
Methods
As the TAT of the pre‐analytical phase is the greatest contributor to TAT, we divided it into sampling, sample transport, and sample preparation times. An additional autoanalyzer was introduced, and its effect on TAT improvement was evaluated with the TAT data of June and July 2020. A real‐time monitoring system was introduced to sort delayed samples, and its effect was assessed with the TAT data of June and July 2021. TAT data from December 2019 to January 2020 were set as baseline controls.
Results
The preparation time comprised the largest proportion of TAT. Although there was a slight decrease in overall TAT after the introduction of the above two strategies, the target TAT achievement rate increased significantly from 78.5% to 88.7% (p < 0.001).
Conclusions
We checked the cause of TAT prolongation and introduced new strategies to improve it. The addition of an autoanalyzer per se was not so effective but was better when combined with the real‐time monitoring system. Such strategies would increase the quality of the laboratory services.
To identify the delayed section, we further divided the pre‐analytical phase into three substeps. Among them, preparation time comprised the largest proportion of TAT. As the samples are rushed early in the morning, we devised a real‐time monitoring system to set the test priority of samples based on the time elapsed and assign them to four autoanalyzers considering their workload.</description><subject>autoanalyzer</subject><subject>Automation</subject><subject>Bar codes</subject><subject>Chi-square test</subject><subject>Information systems</subject><subject>Laboratories</subject><subject>Monitoring systems</subject><subject>outpatient testing</subject><subject>Phlebotomy</subject><subject>priority</subject><subject>real‐time monitoring</subject><subject>turnaround time</subject><subject>Workloads</subject><issn>0887-8013</issn><issn>1098-2825</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kM1KxDAURoMoOI5ufIKAO6HjTdI0yUYYBn8ZcKGuQ9Km2qHTjEmK9O1trWtXd3POx-UgdElgRQDoza5szYrmRcGP0IKAkhmVlB-jBUgpMgmEnaKzGHcAIBUpFuj2NQWT3EfjIk4ex08fkutw6kNngu-7Cqdm73DTYd-ng0mN6xJujfWj5cNwjk5q00Z38XeX6P3-7m3zmG1fHp42621WMiZ4pkqQpjCUCedMRaktbWVzxViteF4J4iwBwYtSsjqnUAhh87qiLOfc8pqN3hJdzbuH4L96F5Pe-enFNmoqKKMKhBIjdT1TZfAxBlfrQ2j2JgyagJ766KmP_u0zwmSGv5vWDf-Q-nmzXc_ODzucZ_A</recordid><startdate>202210</startdate><enddate>202210</enddate><creator>Lee, Seunghoo</creator><creator>Yoon, Sangpil</creator><creator>Lee, Woochang</creator><creator>Chun, Sail</creator><creator>Min, Won‐Ki</creator><general>John Wiley & Sons, Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QP</scope><scope>7T5</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0003-3956-6397</orcidid><orcidid>https://orcid.org/0000-0002-5792-973X</orcidid><orcidid>https://orcid.org/0000-0002-5158-2130</orcidid><orcidid>https://orcid.org/0000-0002-3271-9306</orcidid><orcidid>https://orcid.org/0000-0002-9756-0295</orcidid></search><sort><creationdate>202210</creationdate><title>Strategies to shorten turnaround time in outpatient laboratory</title><author>Lee, Seunghoo ; Yoon, Sangpil ; Lee, Woochang ; Chun, Sail ; Min, Won‐Ki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3375-9c08a6a237eead22bcbdb4933f954d71eb10756c83f420677b4fd23455b5f3a23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>autoanalyzer</topic><topic>Automation</topic><topic>Bar codes</topic><topic>Chi-square test</topic><topic>Information systems</topic><topic>Laboratories</topic><topic>Monitoring systems</topic><topic>outpatient testing</topic><topic>Phlebotomy</topic><topic>priority</topic><topic>real‐time monitoring</topic><topic>turnaround time</topic><topic>Workloads</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Seunghoo</creatorcontrib><creatorcontrib>Yoon, Sangpil</creatorcontrib><creatorcontrib>Lee, Woochang</creatorcontrib><creatorcontrib>Chun, Sail</creatorcontrib><creatorcontrib>Min, Won‐Ki</creatorcontrib><collection>Wiley Online Library (Open Access Collection)</collection><collection>Wiley Online Library (Open Access Collection)</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Immunology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Journal of clinical laboratory analysis</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Seunghoo</au><au>Yoon, Sangpil</au><au>Lee, Woochang</au><au>Chun, Sail</au><au>Min, Won‐Ki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Strategies to shorten turnaround time in outpatient laboratory</atitle><jtitle>Journal of clinical laboratory analysis</jtitle><date>2022-10</date><risdate>2022</risdate><volume>36</volume><issue>10</issue><epage>n/a</epage><issn>0887-8013</issn><eissn>1098-2825</eissn><abstract>Background
Turnaround time (TAT) is one of the most important indicators of laboratory quality. For the outpatient routine chemistry tests whose results are checked by clinicians on the same day, we set a quality goal that >90% of these samples should be reported within 60 min. As more than 20% of the samples failed to achieve this goal in 2020, we introduced an additional autoanalyzer and a real‐time monitoring system to improve this rate.
Methods
As the TAT of the pre‐analytical phase is the greatest contributor to TAT, we divided it into sampling, sample transport, and sample preparation times. An additional autoanalyzer was introduced, and its effect on TAT improvement was evaluated with the TAT data of June and July 2020. A real‐time monitoring system was introduced to sort delayed samples, and its effect was assessed with the TAT data of June and July 2021. TAT data from December 2019 to January 2020 were set as baseline controls.
Results
The preparation time comprised the largest proportion of TAT. Although there was a slight decrease in overall TAT after the introduction of the above two strategies, the target TAT achievement rate increased significantly from 78.5% to 88.7% (p < 0.001).
Conclusions
We checked the cause of TAT prolongation and introduced new strategies to improve it. The addition of an autoanalyzer per se was not so effective but was better when combined with the real‐time monitoring system. Such strategies would increase the quality of the laboratory services.
To identify the delayed section, we further divided the pre‐analytical phase into three substeps. Among them, preparation time comprised the largest proportion of TAT. As the samples are rushed early in the morning, we devised a real‐time monitoring system to set the test priority of samples based on the time elapsed and assign them to four autoanalyzers considering their workload.</abstract><cop>New York</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1002/jcla.24665</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0003-3956-6397</orcidid><orcidid>https://orcid.org/0000-0002-5792-973X</orcidid><orcidid>https://orcid.org/0000-0002-5158-2130</orcidid><orcidid>https://orcid.org/0000-0002-3271-9306</orcidid><orcidid>https://orcid.org/0000-0002-9756-0295</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | autoanalyzer Automation Bar codes Chi-square test Information systems Laboratories Monitoring systems outpatient testing Phlebotomy priority real‐time monitoring turnaround time Workloads |
| title | Strategies to shorten turnaround time in outpatient laboratory |
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