Comparing regression-adjusted mortality to standardized mortality ratios for trauma center profiling.

Lynne Moore, James A Hanley, Alexis F Turgeon, André Lavoie
Author Information
  1. Lynne Moore: Department of Epidemiology and Biostatistics. McGill University, Montreal, Canada.

Abstract

BACKGROUND: Trauma center profiling is commonly performed with Standardized Mortality Ratios (SMRs). However, comparison of SMRs across trauma centers with different case mix can induce confounding leading to biased trauma center ranks. We hypothesized that Regression-Adjusted Mortality (RAM) estimates would provide a more valid measure of trauma center performance than SMRs.
OBJECTIVE: Compare trauma center ranks generated by RAM estimates to those generated by SMRs.
MATERIALS AND METHODS: The study was based on data from a provincial Trauma Registry (1999-2006; n = 88,235). SMRs were derived as the ratio of observed to expected deaths using: (1) the study population as an internal standard, (2) the US National Trauma Data Bank as an external standard. The expected death count was calculated as the sum of mortality probabilities for all patients treated in a hospital conditional on the injury severity score, the revised trauma score, and age. RAM estimates were obtained directly from a hierarchical logistic regression model.
RESULTS: Crude mortality was 5.4% and varied between 1.3% and 13.5% across the 59 trauma centers. When trauma center ranks from internal SMRs and RAM were compared, 49 out of 59 centers changed rank and six centers changed by more than five ranks. When trauma center ranks from external SMRs and RAM were compared, 55 centers changed rank and 17 changed by more than five ranks.
CONCLUSIONS: The results of this study suggest that the use of SMRs to rank trauma centers in terms of mortality may be misleading. RAM estimates represent a potentially more valid method of trauma center profiling.

Keywords

References

  1. J Am Coll Surg. 2001 Sep;193(3):250-4 [PMID: 11548794]
  2. IARC Sci Publ. 1987;(82):1-406 [PMID: 3329634]
  3. J Public Health Med. 2001 Mar;23(1):40-6 [PMID: 11315692]
  4. Health Serv Outcomes Res Methodol. 2003;4(3):135-149 [PMID: 19606272]
  5. J Trauma. 2005 Sep;59(3):698-704 [PMID: 16361915]
  6. J Trauma. 1987 Apr;27(4):370-8 [PMID: 3106646]
  7. Health Aff (Millwood). 2007 Jan-Feb;26(1):75-85 [PMID: 17211016]
  8. BMJ. 2003 Apr 12;326(7393):777-8 [PMID: 12689953]
  9. J Trauma. 1990 Nov;30(11):1356-65 [PMID: 2231804]
  10. Acad Emerg Med. 2004 Feb;11(2):181-6 [PMID: 14759963]
  11. J Trauma. 1992 Aug;33(2):205-11; discussion 211-2 [PMID: 1507282]
  12. Ann Surg. 2010 May;251(5):952-8 [PMID: 20395844]
  13. J Trauma. 2004 May;56(5):1090-6 [PMID: 15179251]
  14. Am J Epidemiol. 1972 Dec;96(6):383-8 [PMID: 4643670]
  15. Int J Epidemiol. 1986 Mar;15(1):8-21 [PMID: 3514499]
  16. J Clin Epidemiol. 1988;41(11):1125-34 [PMID: 3256304]
  17. J Trauma. 1976 Nov;16(11):882-5 [PMID: 994270]
  18. Ann Epidemiol. 1995 Jan;5(1):60-4 [PMID: 7728286]
  19. Lancet. 2004 Apr 3;363(9415):1147-54 [PMID: 15064036]
  20. Ann Surg. 2009 Jun;249(6):1040-6 [PMID: 19474674]
  21. Stat Med. 2000 Apr 30;19(8):1081-8 [PMID: 10790681]
  22. J Trauma. 1989 May;29(5):623-9 [PMID: 2657085]

Word Cloud

Created with Highcharts 10.0.0traumacenterSMRscentersranksRAMmortalityprofilingestimateschangedTraumaMortalitystudyrankacrossvalidgeneratedexpected1internalstandardexternalscore59comparedfiveBACKGROUND:commonlyperformedStandardizedRatiosHowevercomparisondifferentcasemixcaninduceconfoundingleadingbiasedhypothesizedRegression-AdjustedprovidemeasureperformanceOBJECTIVE:CompareMATERIALSANDMETHODS:baseddataprovincialRegistry1999-2006n=88235derivedratioobserveddeathsusing:population2USNationalDataBankdeathcountcalculatedsumprobabilitiespatientstreatedhospitalconditionalinjuryseverityrevisedageobtaineddirectlyhierarchicallogisticregressionmodelRESULTS:Crude54%varied3%135%49six5517CONCLUSIONS:resultssuggestusetermsmaymisleadingrepresentpotentiallymethodComparingregression-adjustedstandardizedratios

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