Predicting trauma inpatient mortality in an administrative database: an investigation of survival risk ratios using New York data.
BACKGROUND
A precise and unbiased measure of injury severity, calculable from administrative data sets, is needed for population-based studies.


METHODS
The 2001 Nationwide Inpatient Sample was used to calculate independent and traditional survival risk ratios. Logistic regression models predicting survival for New York State's Statewide Planning and Research Cooperative System 2003 inpatients (117,630 records) were constructed for both types of survival risk ratios. The contribution of only the worst survival risk ratio (SRR), the two worst SRRs, the three worst, the four worst, and all trauma diagnoses was investigated. The contribution of gender and age to the models was assessed.


RESULTS
Use of the two worst SRRs, gender, and age gives the best prediction of inhospital mortality.


CONCLUSIONS
Inhospital mortality in both trauma centers and in community hospitals can be predicted well from an administrative database by using three predictors--gender, age, and the product of the SRRs for the two diagnoses with the lowest chance of survival.
Hannan
Edward L
EL
Department of Health Policy, Management and Behavior, School of Public Health, University at Albany, State University of New York, NY 12144-3456, USA. elh03@health.state.ny.us
Farrell
Louise Szypulski
LS
D000367:Age Factors; D016208:Databases, Factual; D005260:Female; D006801:Humans; D015601:Injury Severity Score; D016015:Logistic Models; D008297:Male; D008499:Medical Records; D009518:New York / Q000453:epidemiology; D016017:Odds Ratio; D017063:Outcome Assessment, Health Care; D012306:Risk; D012737:Sex Factors; D016019:Survival Analysis; D014947:Wounds and Injuries / Q000145:classification / Q000401:mortality*