A new method for evaluating trauma centre outcome performance: Tram-adjusted mortality estimates

Annals of Surgery

Volumn 251, Issue 5, 2010, Pages 952-958

  Moore, Lynne ^a,b   Hanley, James A ^a   Turgeon, Alexis F ^b   Lavoie, André ^b   Eric, Bergeron ^b,c  

^a MCGILL UNIVERSITY   (Canada)

^b LAVAL UNIVERSITY   (Canada)

^c HÔPITAL CHARLES LEMOYNE   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; EMERGENCY HEALTH SERVICE; HUMAN; INJURY SCALE; MAJOR CLINICAL STUDY; MORTALITY; PRIORITY JOURNAL; RISK FACTOR; STANDARDIZED MORTALITY RATIO;

EID: 77951667179     PISSN: 00034932     EISSN: 15281140     Source Type: Journal    
DOI: 10.1097/SLA.0b013e3181d97589     Document Type: Article

References (60)

1. The enormous human and financial cost of trauma. Sunnybrook Research Institute. Available at: http://www.swri.ca/programs/trauma/. Accessed April 26, 2007.
2. MacKenzie EJ, Rivara FP, Jurkovich GJ, et al. A national evaluation of the effect of trauma-center care on mortality. N Engl J Med. 2006;354:366-378.
3. Jurkovich GJ, Mock C. Systematic review of trauma system effectiveness based on registry comparisons. J Trauma. 1999;47(suppl 3):S46-S55. (Pubitemid 29444362)
4. Iezzoni L. Risk Adjustment for Measuring Health Care Outcomes. 3rd ed. Chicago, IL: Health Administration Press; 2003.
5. Boyd CR, Tolson MA, Copes WS. Evaluating trauma care: the TRISS method. Trauma Score and the Injury Severity Score. J Trauma. 1987;27: 370-378.
6. Champion HR, Copes WS, Sacco WJ, et al. The major trauma outcome study: establishing national norms for trauma care. J Trauma. 1990;30:1356-1365.
7. National Trauma Data Bank. American College of Surgeons Committee on Trauma. 2005. Available at: http://www.facs.org/trauma/ntdb.html. Accessed April 26, 2008.
8. Glance LG, Osler TM, Dick AW. Evaluating trauma center quality: does the choice of the severity-adjustment model make a difference? J Trauma. 2005;58:1265-1271.
9. Bouamra O, Wrotchford A, Hollis S, et al. A new approach to outcome prediction in trauma: a comparison with the TRISS model. J Trauma. 2006;61:701-710.
10. Champion HR, Copes WS, Sacco WJ, et al. Improved predictions from a severity characterization of trauma (ASCOT) over Trauma and Injury Severity Score (TRISS): results of an independent evaluation. J Trauma. 1996;40: 42-48; discussion 48-49.
11. Kilgo PD, Meredith JW, Osler TM. Incorporating recent advances to make the TRISS approach universally available. J Trauma. 2006;60:1002-1008; discussion 1008-1009.
12. West TA, Rivara FP, Cummings P, et al. Harborview assessment for risk of mortality: an improved measure of injury severity on the basis of ICD-9-CM. J Trauma. 2000;49:530-540; discussion 540-541.
13. Moore L, Lavoie A, Turgeon AF, et al. The trauma risk adjustment model: a new model for evaluating trauma care. Ann Surg. 2009;249:1040-1046.
14. National Trauma Data Bank reference manual. American College of Surgeons Committee on Trauma. 2005. Available at: http://www.facs.org/trauma/ntdb. html. Accessed April 26,2008.
15. Demetriades D, Chan L, Velmanos GV, et al. TRISS methodology: an inappropriate tool for comparing outcomes between trauma centers. J Am Coll Surg. 2001;193:250-254.
16. Cayten CG, Stahl WM, Murphy JG, et al. Limitations of the TRISS method for interhospital comparisons: a multihospital study. J Trauma. 1991;31:471-481; discussion 481-482.
17. Dragsted L, Jorgensen J, Jensen NH, et al. Interhospital comparisons of patient outcome from intensive care: importance of lead-time bias. Crit Care Med. 1989;17:418-422.
18. Rosenberg AL, Hofer TP, Strachan C, et al. Accepting critically ill transfer patients: adverse effect on a referral center's outcome and benchmark measures. Ann Intern Med. 2003;138:882-890.
19. Gabbe BJ, Cameron PA, Wolfe R. TRISS: does it get better than this? Acad Emerg Med. 2004;11:181-186.
20. Goldstein H, Spiegelhalter D. League tables and their limitations: statistical issues in comparisons of institutional performance. J R Stat Soc. 1996;159: 385-443. (Pubitemid 126333152)
21. Julious SA, Nicholl J, George S. Why do we continue to use standardized mortality ratios for small area comparisons? J Public Health Med. 2001;23:40-46.
22. Glance LG, Osler T, Shinozaki T. Effect of varying the case mix on the standardized mortality ratio and W statistic: a simulation study. Chest. 2000;117:1112-1117.
23. Breslow NE, Day NE. Statistical Methods in Cancer Research: The Design and Analysis of Cohort Studies. Vol II. Lyon, France: IARC scientific publications; 1987.
24. Trauma ACoSCo. Resources for Optimal Care of the Injured Patient. Chicago, IL: American College of Surgeons; 2006.
25. Lavoie A, Gagne M, Belcaid A, et al. Trauma registry inclusion criteria and severe injury representativeness. J Trauma. 2008;64:551.
26. National Trauma Data Bank report. American College of Surgeons. 2005. Available at: http://www.facs.org/trauma/ntdb.html. Accessed April 27, 2008.
27. AAAM. Abbreviated Injury Scale (AIS) 1990. Morton Grove, IL: AAAM Publications; 1990.
28. Jennett B, Teasdale G. Aspects of coma after severe head injury. Lancet. 1977;1:878-881.
29. Moore L, Lavoie A, LeSage N, et al. Multiple imputation of the Glasgow Coma Score. J Trauma. 2005;59:698-704.
30. Moore L, Lavoie A, LeSage N, et al. Statistical validation of the Revised Trauma Score. J Trauma. 2006;60:305-311.
31. Little RJA, Rubin DB. Statistical Analysis With Missing Data. 2nd ed. New York, NY: Wiley; 2002.
32. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373-383.
33. Romano PS, Roos LL, Jollis JG. Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol. 1993;46:1075-1079; discussion 1081-1090.
34. Moore L, Lavoie A, Sage NL, et al. Using information on preexisting conditions to predict mortality from traumatic injury. Ann Emerg Med. 2008;52:356-364.
35. Jiang J. Linear and Generalized Linear Mixed Models and Their Applications. London, United Kingdom: Springer; 2007.
36. Glance LG, Dick AW, Osler TM, et al. Using hierarchical modeling to measure ICU quality. Intensive Care Med. 2003;29:2223-2229.
37. Zhao D. Logistic regression adjustment of proportions and its macro procedure. SUGI SAS. Available at: http://www2.sas.com/proceedings/sugi22/ POSTERS/PAPER227.PDF. Accessed September 30, 2009.
38. Vittinghoff E, McCulloch CE. Relaxing the rule of ten events per variable in logistic and Cox regression. Am J Epidemiol. 2007;165:710-718.
39. Lilford R, Mohammed MA, Spiegelhalter D, et al. Use and misuse of process and outcome data in managing performance of acute medical care: avoiding institutional stigma. Lancet. 2004;363:1147-1154.
40. Spiegelhalter DJ. Funnel plots for comparing institutional performance. Stat Med. 2005;24:1185-1202.
41. Jones HE, Ohlssen DI, Spiegelhalter DJ. Use of the false discovery rate when comparing multiple health care providers. J Clin Epidemiol. 2008;61:232-240.
42. Jones JM, Redmond AD, Templeton J. Uses and abuses of statistical models for evaluating trauma care. J Trauma. 1995;38:89-93.
43. Moore L, Hanley JA, Lavoie A, et al. Evaluating the validity of multiple imputation for missing physiological data in the national trauma data bank. J Emerg Trauma Shock. 2009;2:73-79.
44. Newgard CD. The validity of using multiple imputation for missing out-of-hospital data in a state trauma registry. Acad Emerg Med. 2006; 13:314-324.
45. D'Errigo P, Tosti ME, Fusco D, et al. Use of hierarchical models to evaluate performance of cardiac surgery centres in the Italian CABG outcome study. BMC Med Res Methodol. 2007;7:29.
46. Chan CK, Feinstein AR, Jekel JF, et al. The value and hazards of standardization in clinical epidemiologic research. J Clin Epidemiol. 1988;41:1125-1134.
47. Osler T, Rutledge R, Deis J, et al. ICISS: an international classification of disease-9 based injury severity score. J Trauma. 1996;41:380-386; discussion 386-388.
48. Shahian DM, Normand SL, Torchiana DF, et al. Cardiac surgery report cards: comprehensive review and statistical critique. Ann Thorac Surg. 2001;72: 2155-2168.
49. Shojania KG, Forster AJ. Hospital mortality: when failure is not a good measure of success. CMAJ. 2008;179:153-157.
50. Nathens AB, Xiong W, Shafi S. Ranking of trauma center performance: the bare essentials. J Trauma. 2008;65:628-635.
51. Shafi S, Nathens AB, Parks J, et al. Trauma quality improvement using risk-adjusted outcomes. J Trauma. 2008;64:599-604; discussion 604-606.
52. Krumholz HM, Wang Y, Mattera JA, et al. An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with an acute myocardial infarction. Circulation. 2006;113: 1683-1692.
53. Mannion R, Davies HT. Payment for performance in health care. BMJ. 2008;336:306-308.
54. Campbell M, Fitzpatrick R, Haines A, et al. Framework for design and evaluation of complex interventions to improve health. BMJ. 2000;321:694-696.
55. Mullins RJ, Mann NC, Hedges JR, et al. Adequacy of hospital discharge status as a measure of outcome among injured patients. JAMA. 1998;279: 1727-1731.
56. Glance LG, Osler TM, Mukamel DB, et al. Impact of statistical approaches for handling missing data on trauma center quality. Ann Surg. 2009;249:143-148.
57. Marx WH, Simon HM, Jumbelic M, et al. Severity of injury is underestimated in the absence of autopsy verification. J Trauma. 2004;57:46-49; discussion 49-50.
58. Edwards SL. Using the Glasgow Coma Scale: analysis and limitations. Br J Nurs. 2001;10:92-101.
59. Marion DW, Carlier PM. Problems with initial Glasgow Coma Scale assessment caused by prehospital treatment of patients with head injuries: results of a national survey. J Trauma. 1994;36:89-95.
60. Quan H, Parsons GA, Ghali WA. Validity of information on comorbidity derived from ICD-9-CM administrative data. Med Care. 2002;40:675-685.