IMP-ICDX: an injury mortality prediction based on ICD-10-CM codes

The International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) Injury Severity Score (ICISS) is a risk adjustment model when injuries are recorded using ICD-9-CM coding. The trauma mortality prediction model (TMPM-ICD9) provides better calibration and discrimination co...

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Veröffentlicht in:World journal of emergency surgery 2019-10, Vol.14 (1), p.46-46, Article 46
Hauptverfasser: Wang, Muding, Qiu, Wusi, Zeng, Yunji, Fan, Wenhui, Lian, Xiao, Shen, Yi
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Sprache:eng
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Zusammenfassung:The International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) Injury Severity Score (ICISS) is a risk adjustment model when injuries are recorded using ICD-9-CM coding. The trauma mortality prediction model (TMPM-ICD9) provides better calibration and discrimination compared with ICISS and injury severity score (ISS). Though TMPM-ICD9 is statistically rigorous, it is not precise enough mathematically and has the tendency to overestimate injury severity. The purpose of this study is to develop a new ICD-10-CM injury model which estimates injury severities for every injury in the ICD-10-CM lexicon by a combination of rigorous statistical probit models and mathematical properties and improves the prediction accuracy. We developed an injury mortality prediction (IMP-ICDX) using data of 794,098 patients admitted to 738 hospitals in the National Trauma Data Bank from 2015 to 2016. Empiric measures of severity for each of the trauma ICD-10-CM codes were estimated using a weighted median death probability (WMDP) measurement and then used as the basis for IMP-ICDX. ISS (version 2005) and the single worst injury (SWI) model were re-estimated. The performance of each of these models was compared by using the area under the receiver operating characteristic (AUC), the Hosmer-Lemeshow (HL) statistic, and the Akaike information criterion statistic. IMP-ICDX exhibits significantly better discrimination (AUC , 0.893, and 95% confidence interval (CI), 0.887 to 0.898; AUC , 0.853, and 95% CI, 0.846 to 0.860; and AUC , 0.886, and 95% CI, 0.881 to 0.892) and calibration (HL , 68, and 95% CI, 36 to 98; HL , 252, and 95% CI, 191 to 310; and HL , 92, and 95% CI, 53 to 128) compared with ISS and SWI. All models were improved after the extension of age, gender, and injury mechanism, but the augmented IMP-ICDX still dominated ISS and SWI by every performance. The IMP-ICDX has a better discrimination and calibration compared to ISS. Therefore, we believe that IMP-ICDX could be a new viable trauma research assessment method.
ISSN:1749-7922
1749-7922
DOI:10.1186/s13017-019-0265-y