A trauma mortality prediction model based on the ICD-10-CM lexicon: TMPM-ICD10. Issue 5 (May 2019)

• Record Type: Journal Article
• Authors: Osler, Turner M.; Glance, Laurent G.; Cook, Alan; Buzas, Jeffrey S.; Hosmer, David W.
• Is Part Of: Journal of trauma and acute care surgery. Volume 86:Issue 5(2019)
• Publication Date: 2019-05
• Subjects: ICD-10-CM -- outcome prediction -- survival model -- regression; Surgical intensive care -- Periodicals; Surgical emergencies -- Periodicals; Wounds and injuries -- Surgery -- Periodicals; 617.026
• DOI: 10.1097/TA.0000000000002194
• Languages: English
• ISSNs: 2163-0755

Abstract

Abstract : BACKGROUND: Outcome prediction models allow risk adjustment required for trauma research and the evaluation of outcomes. The advent of ICD-10-CM has rendered risk adjustment based on ICD-9-CM codes moot, but as yet no risk adjustment model based on ICD-10-CM codes has been described. METHODS: The National Trauma Data Bank provided data from 773, 388 injured patients who presented to one of 747 trauma centers in 2016 with traumatic injuries ICD-10-CM codes and Injury Severity Score (ISS). We constructed an outcome prediction model using only ICD-10-CM acute injury codes and compared its performance with that of the ISS. RESULTS: Compared with ISS, the TMPM-ICD-10 discriminated survivors from non-survivors better (ROC TMPM-ICD-10 = 0.861 [0.860–0.872], ROC [reviever operating curve] ISS = 0.830 [0.823–0.836]), was better calibrated (HL [Hosmer-Lemeshow statistic] TMPM-ICD-10 = 49.01, HL ISS = 788.79), and had a lower Akaike information criteria (AIC TMPM-ICD10 = 30579.49; AIC ISS = 31802.18). CONCLUSIONS: Because TMPM-ICD10 provides better discrimination and calibration than the ISS and can be computed without recourse to Abbreviated Injury Scale coding, the TMPM-ICD10 should replace the ISS as the standard measure of overall injury severity for data coded in the ICD-10-CM lexicon. LEVEL OF EVIDENCE: Prognostic/Epidemiologic, level II. Abstract : Supplemental digital content is available in the text.