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Improved Risk Adjustment in Public Reporting: Coronary Artery Bypass Graft Surgical Site Infections

Published online by Cambridge University Press:  02 January 2015

Sandra I. Berríos-Torres*
Affiliation:
Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
Yi Mu
Affiliation:
Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
Jonathan R. Edwards
Affiliation:
Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
Teresa C. Horan
Affiliation:
Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
Scott K. Fridkin
Affiliation:
Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
*
1600 Clifton Road NE MS A-31, Atlanta, GA 30329 (zbn6@cdc.gov)

Abstract

Objective.

The objective was to develop a new National Healthcare Safety Network (NHSN) risk model for sternal, deep incisional, and organ/space (complex) surgical site infections (SSIs) following coronary artery bypass graft (CABG) procedures, detected on admission and readmission, consistent with public reporting requirements.

Patients and Setting.

A total of 133,503 CABG procedures with 4,008 associated complex SSIs reported by 293 NHSN hospitals in the United States.

Methods.

CABG procedures performed from January 1, 2006, through December 31, 2008, were analyzed. Potential SSI risk factors were identified by univariate analysis. Multivariate analysis with forward stepwise logistic regression modeling was used to develop the new model. The c-index was used to compare the predictive power of the new and NHSN risk index models.

Results.

Multivariate analysis independent risk factors included ASA score, procedure duration, female gender, age, and medical school affiliation. The new risk model has significantly improved predictive performance over the NHSN risk index (c-index, 0.62 and 0.56, respectively).

Conclusions.

Traditionally, the NHSN surveillance system has used a risk index to provide procedure-specific risk-stratified SSI rates to hospitals. A new CABG sternal, complex SSI risk model developed by multivariate analysis has improved predictive performance over the traditional NHSN risk index and is being considered for endorsement as a measure for public reporting.

Type
Original Articles
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2012

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References

1.De Frances, CJ, Lucas, CA, Buie, VC, Golosinskiy, A. 2006 National Hospital Discharge Survey. National Health Statistics Reports, no. 5, July 30, 2008. http://www.cdc.gov/nchs/data/nhsr/nhsr005.pdf. Accessed November 12, 2010.Google Scholar
2.Horan, TC, Gaynes, RP, Martone, WJ, Jarvis, WR, Emori, TG. CDC definitions of nosocomial surgical site infections, 1992: a modification of CDC definitions of surgical wound infections. Infect Control Hosp Epidemiol 1992;13:606608.Google Scholar
3.Abboud, CS, Wey, SB, Baltar, VT. Risk factors for mediastinitis after cardiac surgery. Ann Thorac Surg 2004;77:676683.CrossRefGoogle ScholarPubMed
4.The Parisian Mediastinitis Study Group. Risk factors for deep sternal wound infections after sternotomy: a prospective, multicenter study. J Thorac Cardiovasc Surg 2006;111:12001207.Google Scholar
5.Risnes, I, Abdelnoor, M, Almdahl, SM, Svennevig, JL. Mediastinitis after coronary artery bypass grafting risk factors and long-term survival. Ann Thorac Surg 2010;89:15021510.CrossRefGoogle ScholarPubMed
6.Olsen, MA, Lock-Buckley, P, Hopkins, D, Polish, LB, Sundt, TM, Fraser, VJ. The risk factors for deep and superficial chest surgical-site infections after coronary artery bypass graft surgery are different. J Thorac Cardiovasc Surg 2002;124:136145.Google Scholar
7.Hollenbeak, CS, Murphy, DM, Koenig, S, Woodward, RS, Dunagan, WC, Fraser, VJ. The clinical and economic impact of deep chest surgical site infections following coronary artery bypass graft surgery. Chest 2000;118:397402.Google Scholar
8.Zerr, KJ, Furnary, AP, Grunkemeier, GL, Bookin, S, Kanhere, V, Starr, A. Glucose control lowers the risk of wound infection in diabetics after open heart operations. Ann Thorac Surg 1997;63: 356361.CrossRefGoogle ScholarPubMed
9.Harrington, G, Russo, P, Spelman, D, et al. Surgical-site infection rates and risk factor analysis in coronary artery bypass graft surgery. Infect Control Hosp Epidemiol 2004;25:472476.CrossRefGoogle ScholarPubMed
10.Braxton, JH, Marrin, CAS, McGrath, PD, et al. 10 year follow-up of patients with and without medisatinitis. Semin Thorac Cardiovasc Surg 2004;16:7076.Google Scholar
11.Russo, PL, Spelman, DW. A new surgical-site infection risk index using risk factors identified by multivariate analysis for patients undergoing coronary artery bypass graft surgery. Infect Control Hosp Epidemiol 2002;23:372376.CrossRefGoogle ScholarPubMed
12.Haley, RW, Culver, DH, White, JW, et al. The efficacy of infection surveillance and control programs in preventing nosocomial infections in United States hospitals. Am J Epidemiol 1985;121: 182205.Google Scholar
13.Brandt, C, Hansen, S, Sohr, D, Daschner, F, Ruden, H, Gastmeier, P. Finding a method for optimizing risk adjustment when comparing surgical-site infection rates. Infect Control Hosp Epidemiol 2004;25:313318.Google Scholar
14.American Society of Anesthesiologists. New classification of physical status. Anesthesiology 1963;24:111.Google Scholar
15.Culver, DH, Horan, TC, Gaynes, RP, et al. Surgical wound-infection rates by wound class, operative procedure, and patient risk index. Am J Med 1991;91:S152S157.CrossRefGoogle ScholarPubMed
16.Roy, MC, Herwaldt, LA, Embrey, R, Kuhns, K, Wenzel, RP, Perl, TM. Does the Centers for Disease Control's NNIS System risk index stratify patients undergoing cardiothoracic operations by their risk of surgical-site infection? Infect Control Hosp Epidemiol 2000;21:186190.CrossRefGoogle ScholarPubMed
17.Friedman, ND, Bull, AL, Russo, PL, Gurrin, L, Richards, M. Performance of the National Nosocomial Infections Surveillance risk index in predicting surgical site infection in Australia. Infect Control Hosp Epidemiol 2007;28:5559.Google Scholar
18.Gaynes, RP. Surgical-site infections (SSI) and the NNIS SSI risk index, part II: room for improvement. Infect Control Hosp Epidemiol 2001;22:268272.Google Scholar
19.Association for Professionals in Infection Control. HAI Reporting Laws and Regulation 2010. http://www.apic.org/Resource_/TinyMceFileManager/Advocacy-PDFs/HAI_map.gif. Accessed March 5, 2012.Google Scholar
20.US Department of Health and Human Services. HHS Action Plan to Prevent Healthcare Associated Infections: Appendix G. http://www.hhs.gov/ash/initiatives/hai/index.html. Accessed July 28, 2010.Google Scholar
21.Centers for Medicare and Medicaid Services. 42 CFR Parts 412, 413, 415, et al. Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long Term Care Hospital Prospective Payment System Changes and FY2011 Rates; Provider Agreements and Supplier Approvals; and Hospital Conditions of Participation for Rehabilitation and Respiratory Care Services; Medicaid Program: Accreditation for Providers of Inpatient Psychiatric Services; Final Rule. Federal Register, Rules and Regulations. Washington, DC: Department of Health and Human Services, 2010;75(157):50041-50681. http://edocket.access.gpo.gov/2010/pdf/2010-19092.pdf. Accessed November 3, 2010.Google Scholar
22.Anderson, DJ, Chen, LF, Sexton, DJ, Kaye, KS. Complex surgical site infections and the devilish details of risk adjustment: important implications for public reporting. Infect Control Hosp Epidemiol 2008;29:941946.Google Scholar
23.Shahian, DM, O'Brien, SM, Filardo, G, et al. The Society of Tho rack Surgeons 2008 cardiac surgery risk models. 1. Coronary artery bypass grafting surgery. Ann Thorac Surg 2009;88:S2S22.CrossRefGoogle Scholar
24.Friedman, ND, Bull, AL, Russo, PL, et al. An alternative scoring system to predict risk for surgical site infection complicating coronary artery bypass graft surgery. Infect Control Hosp Epidemiol 2007;28:11621168.CrossRefGoogle ScholarPubMed
25.Paul, M, Raz, A, Leibovici, L, Madar, H, Holinger, R, Rubinovitch, B. Sternal wound infection after coronary artery bypass graft surgery: validation of existing risk scores. J Thorac Cardiovasc Surg 2007;133:397403.Google Scholar
26.Edwards, JR, Peterson, KD, Mu, Y, et al. National Healthcare Safety Network (NHSN) report: data summary for 2006 through 2008, issued December 2009. Am J Infect Control 2009;37: 783805.Google Scholar
27.Centers for Disease Control and Prevention. National Healthcare Safety Network, http://www.cdc.gov/nhsn/. Accessed June 26, 2010.Google Scholar
28.Centers for Disease Control and Prevention. National Healthcare Safety Network: Denominator for Procedure Form. http://www.cdc.gov/nhsn/forms/57.121_DenomProc_BIANK.pdf. Accessed November 12, 2010.Google Scholar
29.Hanley, JA, McNeil, BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983;148:839843.Google Scholar
30.Friedman, ND, Russo, PL, Bull, AL, Richards, MJ, Kelly, H. Validation of coronary artery bypass graft surgical site infection surveillance data from a statewide surveillance system in Australia. Infect Control Hosp Epidemiol 2007;28:812817.CrossRefGoogle ScholarPubMed
31.Yokoe, DS, Noskin, GA, Cunningham, SM, et al. Enhanced identification of postoperative infections among inpatients. Emerg Infect Dis 2004;10:19241930.Google Scholar
32.Cardo, DM, Falk, PS, Mayhall, CG. Validation of surgical wound surveillance. Infect Control Hosp Epidemiol 1993;14:211215.CrossRefGoogle ScholarPubMed
33.Petrosillo, N, Drapeau, CMJ, Nicastri, E, et al. Surgical site infections in Italian hospitals: a prospective multicenter study. BMC Infect Dis 2008;8:34.Google Scholar
34.National Quality Forum. National Voluntary Consensus Standards for the Reporting of Healthcare-Associated Infection Data. http://www.qualityforum.org/Publications/2008/03/National_Voluntary_Consensus_Standards_for_the_Reporting_of_Healthcare-Associated_Infection_Data.aspx. Accessed August 9, 2010.Google Scholar
35.Society for Healthcare Epidemiology of America. Essentials of Public Reporting of Healthcare-Associated Infections: A Tool Kit. http://www.shea-online.org/Assets/files/Essentials_of_Public_Reporting_Tool_Kit.pdf. Accessed July 22, 2010.Google Scholar
36.Liddell, FDK. Simple exact analysis of the standardized mortality ratio. J Epidemiol Community Health 1984;38:8588.Google Scholar
37.Rioux, C, Grandbastien, B, Astagneau, P. The standardized incidence ratio as a reliable tool for surgical site infection surveillance. Infect Control Hosp Epidemiol 2006;27:817824.Google Scholar
38.Geubbels, E, Grobbee, DE, Vandenbroucke-Grauls, C, Wille, JC, de Boer, AS. Improved risk adjustment for comparison of surgical site infection rates. Infect Control Hosp Epidemiol 2006;27: 13301339.CrossRefGoogle ScholarPubMed
39.Neumayer, L, Hosokawa, P, Itani, K, El-Tamer, M, Henderson, WG, Khuri, SF. Multivariable predictors of postoperative surgical site infection after general and vascular surgery: results from the patient safety in surgery study. J Am Coll Surg 2007;204: 11781187.Google Scholar