TMPM-ICD9: a trauma mortality prediction model based on ICD-9-CM codes.
OBJECTIVE
To develop and validate a new ICD-9 injury model that uses regression modeling, as opposed to a simple ratio measurement, to estimate empiric injury severities for each of the injuries in the ICD-9-CM lexicon.


BACKGROUND
The American College of Surgeons now requires International Classification of diseases ninth Edition (ICD-9-CM) codes for injury coding in the National Trauma Databank. International Classification of diseases ninth Edition Injury Severity Score (ICISS) is the best-known risk-adjustment model when injuries are recorded using ICD-9-CM coding, and would likely be used to risk-adjust outcome measures for hospital trauma report cards. ICISS, however, has been criticized for its poor calibration.


METHODS
We developed and validated a new ICD-9 injury model using data on 749,374 patients admitted to 359 hospitals in the National Trauma Databank (version 7.0). Empiric measures of injury severity for each of the trauma ICD-9-CM codes were estimated using a regression-based approach, and then used as the basis for a new Trauma Mortality Prediction Model (TMPM-ICD9). ICISS and the Single-Worst Injury (SWI) model were also re-estimated. The performance of each of these models was compared using the area under the receiver operating characteristic (ROC), the Hosmer-Lemeshow statistic, and the Akaike information criterion statistic.


RESULTS
TMPM-ICD9 exhibits significantly better discrimination (ROCTMPM = 0.880 [0.876-0.883]; ROCICISS = 0.850 [0.846-0.855]; ROCSWI = 0.862 [0.858-0.867]) and calibration (HLTMPM = 29.3 [12.1-44.1]; HLICISS = 231 [176-279]; HLSWI = 462 [380-548]) compared with both ICISS and the Single Worst Injury model. All models were improved with the addition of age, gender, and mechanism of injury, but TMPM-ICD9 continued to demonstrate superior model performance.


CONCLUSIONS
Because TMPM-ICD9 uniformly out-performs ICISS and the SWI model, it should be used in preference to ICISS for risk-adjusting trauma outcomes when injuries are recorded using ICD9-CM codes.
Glance
Laurent G
LG
Department of Anesthesiology, University of Rochester School of Medicine, Rochester, New York 14642, USA. Laurent_Glance@urmc.rochester.edu
Osler
Turner M
TM
Mukamel
Dana B
DB
Meredith
Wayne
W
Wagner
Jacob
J
Dick
Andrew W
AW
D000328:Adult; D016208:Databases, Factual; D005260:Female; D006801:Humans; D038801:International Classification of Diseases; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012189:Retrospective Studies; D020379:Risk Adjustment; D015599:Trauma Severity Indices; D014947:Wounds and Injuries / Q000401:mortality*