Comparison of Outcome Tools Used to Test Mass-Casualty Algorithms in the Pediatric Population

Introduction:Mass-casualty incident (MCI) algorithms are used to sort large numbers of patients rapidly into four basic categories based on severity. To date, there is no consensus on the best method to test the accuracy of an MCI algorithm in the pediatric population, nor on the agreement between d...

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Veröffentlicht in:Prehospital and disaster medicine 2021-12, Vol.36 (6), p.719-723
Hauptverfasser: Donofrio, J. Joelle, Shaban, Alaa, Kaji, Amy H., Santillanes, Genevieve, Cicero, Mark X., Chang, Todd P., Gausche-Hill, Marianne, Claudius, Ilene A.
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container_end_page 723
container_issue 6
container_start_page 719
container_title Prehospital and disaster medicine
container_volume 36
creator Donofrio, J. Joelle
Shaban, Alaa
Kaji, Amy H.
Santillanes, Genevieve
Cicero, Mark X.
Chang, Todd P.
Gausche-Hill, Marianne
Claudius, Ilene A.
description Introduction:Mass-casualty incident (MCI) algorithms are used to sort large numbers of patients rapidly into four basic categories based on severity. To date, there is no consensus on the best method to test the accuracy of an MCI algorithm in the pediatric population, nor on the agreement between different tools designed for this purpose.Study Objective:This study is to compare agreement between the Criteria Outcomes Tool (COT) to previously published outcomes tools in assessing the triage category applied to a simulated set of pediatric MCI patients.Methods:An MCI triage category (black, red, yellow, and green) was applied to patients from a pre-collected retrospective cohort of pediatric patients under 14 years of age brought in as a trauma activation to a Level I trauma center from July 2010 through November 2013 using each of the following outcome measures: COT, modified Baxt score, modified Baxt combined with mortality and/or length-of-stay (LOS), ambulatory status, mortality alone, and Injury Severity Score (ISS). Descriptive statistics were applied to determine agreement between tools.Results:A total of 247 patients were included, ranging from 25 days to 13 years of age. The outcome of mortality had 100% agreement with the COT black. The “modified Baxt positive and alive” outcome had the highest agreement with COT red (65%). All yellow outcomes had 47%-53% agreement with COT yellow. “Modified Baxt negative and
doi_str_mv 10.1017/S1049023X2100100X
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Joelle ; Shaban, Alaa ; Kaji, Amy H. ; Santillanes, Genevieve ; Cicero, Mark X. ; Chang, Todd P. ; Gausche-Hill, Marianne ; Claudius, Ilene A.</creator><creatorcontrib>Donofrio, J. Joelle ; Shaban, Alaa ; Kaji, Amy H. ; Santillanes, Genevieve ; Cicero, Mark X. ; Chang, Todd P. ; Gausche-Hill, Marianne ; Claudius, Ilene A.</creatorcontrib><description>Introduction:Mass-casualty incident (MCI) algorithms are used to sort large numbers of patients rapidly into four basic categories based on severity. To date, there is no consensus on the best method to test the accuracy of an MCI algorithm in the pediatric population, nor on the agreement between different tools designed for this purpose.Study Objective:This study is to compare agreement between the Criteria Outcomes Tool (COT) to previously published outcomes tools in assessing the triage category applied to a simulated set of pediatric MCI patients.Methods:An MCI triage category (black, red, yellow, and green) was applied to patients from a pre-collected retrospective cohort of pediatric patients under 14 years of age brought in as a trauma activation to a Level I trauma center from July 2010 through November 2013 using each of the following outcome measures: COT, modified Baxt score, modified Baxt combined with mortality and/or length-of-stay (LOS), ambulatory status, mortality alone, and Injury Severity Score (ISS). Descriptive statistics were applied to determine agreement between tools.Results:A total of 247 patients were included, ranging from 25 days to 13 years of age. The outcome of mortality had 100% agreement with the COT black. The “modified Baxt positive and alive” outcome had the highest agreement with COT red (65%). All yellow outcomes had 47%-53% agreement with COT yellow. “Modified Baxt negative and &lt;24 hours LOS” had the highest agreement with the COT green at 89%.Conclusions:Assessment of algorithms for triaging pediatric MCI patients is complicated by the lack of a gold standard outcome tool and variability between existing measures.</description><identifier>ISSN: 1049-023X</identifier><identifier>EISSN: 1945-1938</identifier><identifier>DOI: 10.1017/S1049023X2100100X</identifier><language>eng</language><publisher>New York, USA: Cambridge University Press</publisher><subject>Agreements ; Algorithms ; Blood pressure ; Emergency medical care ; Health technology assessment ; Lifesaving ; Mortality ; Original Research ; Patients ; Pediatrics ; Trauma</subject><ispartof>Prehospital and disaster medicine, 2021-12, Vol.36 (6), p.719-723</ispartof><rights>The Author(s), 2021. Published by Cambridge University Press on behalf of the World Association for Disaster and Emergency Medicine</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c302t-1bc6af44a7a556c8f7f9ca4e3a9ce7f04512fc2a524d899bc422f5e45c7195373</cites><orcidid>0000-0002-4508-2551 ; 0000-0002-3292-9696</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S1049023X2100100X/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,314,776,780,27903,27904,55606</link.rule.ids></links><search><creatorcontrib>Donofrio, J. Joelle</creatorcontrib><creatorcontrib>Shaban, Alaa</creatorcontrib><creatorcontrib>Kaji, Amy H.</creatorcontrib><creatorcontrib>Santillanes, Genevieve</creatorcontrib><creatorcontrib>Cicero, Mark X.</creatorcontrib><creatorcontrib>Chang, Todd P.</creatorcontrib><creatorcontrib>Gausche-Hill, Marianne</creatorcontrib><creatorcontrib>Claudius, Ilene A.</creatorcontrib><title>Comparison of Outcome Tools Used to Test Mass-Casualty Algorithms in the Pediatric Population</title><title>Prehospital and disaster medicine</title><addtitle>Prehosp. Disaster med</addtitle><description>Introduction:Mass-casualty incident (MCI) algorithms are used to sort large numbers of patients rapidly into four basic categories based on severity. To date, there is no consensus on the best method to test the accuracy of an MCI algorithm in the pediatric population, nor on the agreement between different tools designed for this purpose.Study Objective:This study is to compare agreement between the Criteria Outcomes Tool (COT) to previously published outcomes tools in assessing the triage category applied to a simulated set of pediatric MCI patients.Methods:An MCI triage category (black, red, yellow, and green) was applied to patients from a pre-collected retrospective cohort of pediatric patients under 14 years of age brought in as a trauma activation to a Level I trauma center from July 2010 through November 2013 using each of the following outcome measures: COT, modified Baxt score, modified Baxt combined with mortality and/or length-of-stay (LOS), ambulatory status, mortality alone, and Injury Severity Score (ISS). Descriptive statistics were applied to determine agreement between tools.Results:A total of 247 patients were included, ranging from 25 days to 13 years of age. The outcome of mortality had 100% agreement with the COT black. The “modified Baxt positive and alive” outcome had the highest agreement with COT red (65%). All yellow outcomes had 47%-53% agreement with COT yellow. “Modified Baxt negative and &lt;24 hours LOS” had the highest agreement with the COT green at 89%.Conclusions:Assessment of algorithms for triaging pediatric MCI patients is complicated by the lack of a gold standard outcome tool and variability between existing measures.</description><subject>Agreements</subject><subject>Algorithms</subject><subject>Blood pressure</subject><subject>Emergency medical care</subject><subject>Health technology assessment</subject><subject>Lifesaving</subject><subject>Mortality</subject><subject>Original Research</subject><subject>Patients</subject><subject>Pediatrics</subject><subject>Trauma</subject><issn>1049-023X</issn><issn>1945-1938</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp1UMtKAzEUDaJgrX6Au4AbN6N5zjTLUnxBpQVb6EaGNJO0KTOTMcks-vemtCAowuXeC-fB4QBwi9EDRrh4_MCICUToimCE0qzOwAALxjMs6Og8_QnODvgluAphhxARnOQD8DlxTSe9Da6FzsBZH5VrNFw4Vwe4DLqC0cGFDhG-yxCyiQy9rOMejuuN8zZumwBtC-NWw7murIzeKjh3XV_LaF17DS6MrIO-Od0hWD4_LSav2XT28jYZTzNFEYkZXqtcGsZkITnP1cgURijJNJVC6cIgxjExikhOWDUSYq0YIYZrxlWBBacFHYL7o2_n3Vef0paNDUrXtWy160NJeCFyetiJeveLunO9b1O6xBICoYIlyyHAR5byLgSvTdl520i_LzEqD4WXfwpPGnrSyGbtbbXRP9b_q74B3j-CeQ</recordid><startdate>20211201</startdate><enddate>20211201</enddate><creator>Donofrio, J. 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Joelle</creatorcontrib><creatorcontrib>Shaban, Alaa</creatorcontrib><creatorcontrib>Kaji, Amy H.</creatorcontrib><creatorcontrib>Santillanes, Genevieve</creatorcontrib><creatorcontrib>Cicero, Mark X.</creatorcontrib><creatorcontrib>Chang, Todd P.</creatorcontrib><creatorcontrib>Gausche-Hill, Marianne</creatorcontrib><creatorcontrib>Claudius, Ilene A.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing &amp; Allied Health Database</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Public Health Database</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 One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>Medical Database</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><jtitle>Prehospital and disaster medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Donofrio, J. Joelle</au><au>Shaban, Alaa</au><au>Kaji, Amy H.</au><au>Santillanes, Genevieve</au><au>Cicero, Mark X.</au><au>Chang, Todd P.</au><au>Gausche-Hill, Marianne</au><au>Claudius, Ilene A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of Outcome Tools Used to Test Mass-Casualty Algorithms in the Pediatric Population</atitle><jtitle>Prehospital and disaster medicine</jtitle><addtitle>Prehosp. Disaster med</addtitle><date>2021-12-01</date><risdate>2021</risdate><volume>36</volume><issue>6</issue><spage>719</spage><epage>723</epage><pages>719-723</pages><issn>1049-023X</issn><eissn>1945-1938</eissn><abstract>Introduction:Mass-casualty incident (MCI) algorithms are used to sort large numbers of patients rapidly into four basic categories based on severity. 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issn 1049-023X
1945-1938
language eng
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source Cambridge Journals
subjects Agreements
Algorithms
Blood pressure
Emergency medical care
Health technology assessment
Lifesaving
Mortality
Original Research
Patients
Pediatrics
Trauma
title Comparison of Outcome Tools Used to Test Mass-Casualty Algorithms in the Pediatric Population
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