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By Asensio J.A., Trunkey D.D.

Evidence-based method of difficulties encountered in trauma and demanding care surgical occasions

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Extra resources for Current Therapy of Trauma and Surgical Critical Care

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The Northern New England cardiovascular Disease Study Group. JAMA 275:841–846, 1996. 48. Khuri SF, Daley J, Henderson WG: The comparative assessment and improvement of quality of surgical care in the Department of Veterans Affairs. Arch Surg 137:20–27, 2002. 49. Steiner SH, Cook RJ, et al: Monitoring surgical performance using riskadjusted cumulative sum charts. Biostatistics 1(4):441–452, 2000. 50. Rogers CA, Reeves BC, Caputo M, et al: Control chart methods for monitoring cardiac surgical performance and their interpretation.

37. Terrin N, Schmid CH, Griffith JL, et al: External validity of predictive models: a comparison of logistic regression classification trees and neural networks. J Clin Epidemiol 56:721–729, 2003. 38. DiRusso SM, Sullivan T, Golly C, et al: An artificial neural network as a model for prediction of survival in trauma patients: validation for a regional trauma area. J Trauma Inj Infect Crit Care 49:212–221, 2000. 39. Flora JD: A method for comparing survival of burn patients to a standard survival curve.

Washington, DC: National Academy Press, 2000. 41. Roland M: Linking physicians’ pay to the quality of care—a major experiment in the United Kingdom. N Engl J Med;351:1448–1454, 2004. 42. Goldstein H, Spiegelhalter DJ: League tables and their limitations: statistical issues in comparisons of institutional performance. J R Stat Soc A 159: 385–443, 1996. 43. Normand ST, Glickman ME, Gatsonis CA: Statistical methods for profiling providers of medical care: issues and applications. J Am Stat Assoc 92: 803–814, 1997.

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