84 Comparison of manually and algorithm derived injury severity scores

BackgroundVarious attempts have been made to reduce the administrative burden of manually assigning Abbreviated Injury Severity (AIS) codes to derive Injury Severity Scores (ISS) in trauma registry data. The accuracy of the resulting measures remains unclear, especially in the New Zealand (NZ) conte...

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Published inInjury prevention Vol. 28; no. Suppl 2; p. A10
Main Authors Montoya, Luisa, Davie, Gabrielle, Kool, Doctor Bridget, Dicker, Bridget
Format Journal Article
LanguageEnglish
Published London BMJ Publishing Group Ltd 01.11.2022
BMJ Publishing Group LTD
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ISSN1353-8047
1475-5785
DOI10.1136/injuryprev-2022-safety2022.30

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Abstract BackgroundVarious attempts have been made to reduce the administrative burden of manually assigning Abbreviated Injury Severity (AIS) codes to derive Injury Severity Scores (ISS) in trauma registry data. The accuracy of the resulting measures remains unclear, especially in the New Zealand (NZ) context. The aim of this study was to compare ISS derived from hospital discharge International Classification of Diseases (ICD-10-AM) codes with ISS recorded in the NZ Major Trauma Registry (NZ-MTR).MethodsIndividuals admitted to hospital and enrolled in the NZ-MTR between 1 December 2016 and 30 November 2018 were included. ISS were calculated using a modified ICD/AIS mapping tool (ICD-ISS). The agreement between MTR-ISS and ICD-ISS for raw scores was assessed by Bland-Altman charts and the Intraclass Correlation Coefficient (ICC). Analysis was conducted by gender, age, ethnicity, and mechanism of injury.Results3,154 patients fulfilled the inclusion criteria. The ICC for agreement between MTR-ISS and ICD-ISS was 0.40 (95% CI: 0.37–0.43), indicating poor agreement. The Bland-Altman plot showed a bias toward lower ISS by the ICD-ISS than the MTR-ISS (average difference was 1.79±10.02). A moderate agreement (ICC=0.50, 95%CI: 0.40–0.60) between MTR-ISS and ICD-ISS was found in the paediatric population (<15 years). Differences by mechanism of injury were observed.ConclusionThe overall agreement between MTR-ISS and ICD-ISS was poor. On average, the ICD/AIS mapping tool tended to underestimate ISS, with a few exceptions.Learning OutcomesFurther modifications are needed to current algorithms to develop higher alignment with current manual calculations.
AbstractList BackgroundVarious attempts have been made to reduce the administrative burden of manually assigning Abbreviated Injury Severity (AIS) codes to derive Injury Severity Scores (ISS) in trauma registry data. The accuracy of the resulting measures remains unclear, especially in the New Zealand (NZ) context. The aim of this study was to compare ISS derived from hospital discharge International Classification of Diseases (ICD-10-AM) codes with ISS recorded in the NZ Major Trauma Registry (NZ-MTR).MethodsIndividuals admitted to hospital and enrolled in the NZ-MTR between 1 December 2016 and 30 November 2018 were included. ISS were calculated using a modified ICD/AIS mapping tool (ICD-ISS). The agreement between MTR-ISS and ICD-ISS for raw scores was assessed by Bland-Altman charts and the Intraclass Correlation Coefficient (ICC). Analysis was conducted by gender, age, ethnicity, and mechanism of injury.Results3,154 patients fulfilled the inclusion criteria. The ICC for agreement between MTR-ISS and ICD-ISS was 0.40 (95% CI: 0.37–0.43), indicating poor agreement. The Bland-Altman plot showed a bias toward lower ISS by the ICD-ISS than the MTR-ISS (average difference was 1.79±10.02). A moderate agreement (ICC=0.50, 95%CI: 0.40–0.60) between MTR-ISS and ICD-ISS was found in the paediatric population (<15 years). Differences by mechanism of injury were observed.ConclusionThe overall agreement between MTR-ISS and ICD-ISS was poor. On average, the ICD/AIS mapping tool tended to underestimate ISS, with a few exceptions.Learning OutcomesFurther modifications are needed to current algorithms to develop higher alignment with current manual calculations.
Author Dicker, Bridget
Montoya, Luisa
Davie, Gabrielle
Kool, Doctor Bridget
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Copyright Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.
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Snippet BackgroundVarious attempts have been made to reduce the administrative burden of manually assigning Abbreviated Injury Severity (AIS) codes to derive Injury...
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SubjectTerms Abstracts
Agreements
Algorithms
Correlation coefficient
Injuries
Injury prevention
Pediatrics
Trauma
Title 84 Comparison of manually and algorithm derived injury severity scores
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