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 in | Injury prevention Vol. 28; no. Suppl 2; p. A10 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
BMJ Publishing Group Ltd
01.11.2022
BMJ Publishing Group LTD |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1353-8047 1475-5785 |
| DOI | 10.1136/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. |
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| 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. 2022 Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ. |
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| DOI | 10.1136/injuryprev-2022-safety2022.30 |
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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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