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The Likelihood of Hospital Readmission Among Patients With Hospital-Onset Central Line–Associated Bloodstream Infections

Published online by Cambridge University Press:  20 May 2015

Carolyn J. Khong
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
James Baggs*
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
David Kleinbaum
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia Rollins School of Public Health, Emory University, Atlanta, Georgia. (C.K. is now affiliated with CHOC Children’s Hospital, Orange County, California.)
Ronda Cochran
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
John A. Jernigan
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
*
Address correspondence to James Baggs, PhD, Centers for Disease Control and Prevention, 1600 Clifton Rd, MS: A31, Atlanta, GA 30333 (jbaggs@cdc.gov).

Abstract

OBJECTIVE

To determine whether central line–associated bloodstream infections (CLABSIs) increase the likelihood of readmission.

DESIGN

Retrospective matched cohort study for the years 2008–2009.

SETTING

Acute care hospitals.

PARTICIPANTS

Medicare recipients. CLABSI and readmission status were determined by linking National Healthcare Safety Network surveillance data to the Centers for Medicare and Medicaid Services’ Medical Provider and Analysis Review in 8 states. Frequency matching was used on International Classification of Diseases, Ninth Revision, Clinical Modification procedure code category and intensive care unit status.

METHODS

We compared the rate of readmission among patients with and without CLABSI during an index hospitalization. Cox proportional hazard analysis was used to assess rate of readmission (the first hospitalization within 30 days after index discharge). Multivariate models included the following covariates: race, sex, length of index hospitalization stay, central line procedure code, Gagne comorbidity score, and individual chronic conditions.

RESULTS

Of the 8,097 patients, 2,260 were readmitted within 30 days (27.9%). The rate of first readmission was 7.1 events/person-year for CLABSI patients and 4.3 events/person-year for non-CLABSI patients (P<.001). The final model revealed a small but significant increase in the rate of 30-day readmissions for patients with a CLABSI compared with similar non-CLABSI patients. In the first readmission for CLABSI patients, we also observed an increase in diagnostic categories consistent with CLABSI, including septicemia and complications of a device.

CONCLUSIONS

Our analysis found a statistically significant association between CLABSI status and readmission, suggesting that CLABSI may have adverse health impact that extends beyond hospital discharge.

Infect Control Hosp Epidemiol 2015;36(8):886–892

Type
Original Articles
Copyright
© 2015 by The Society for Healthcare Epidemiology of America. All rights reserved 

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Footnotes

Presented in part: IDWeek 2013; San Francisco, California; October 2–6, 2013 (poster 187).

References

1. Magill, SS, Edwards, JR, Bamberg, W, et al. Multistate point-prevalence survey of health care-associated infections. N Engl J Med 2014;370:11981208.CrossRefGoogle ScholarPubMed
2. Scott, RD II. The Direct Medical Costs of Healthcare-Associated Infections in U.S. Hospitals and the Benefits of Prevention. Atlanta, GA: Centers for Disease Control and Prevention, 2009.Google Scholar
3. Wise, ME, Scott, RD 2nd, Baggs, JM, et al. National estimates of central line–associated bloodstream infections in critical care patients. Infect Control Hosp Epidemiol 2013;34:547554.CrossRefGoogle ScholarPubMed
4. 2012 National and State Healthcare-Associated Infections Progress Report. Atlanta, GA: Centers for Disease Control and Prevention, 2014.Google Scholar
5. Jarvis, WR. Selected aspects of the socioeconomic impact of nosocomial infections: morbidity, mortality, cost, and prevention. Infect Control Hosp Epidemiol 1996;17:552557.CrossRefGoogle ScholarPubMed
6. Stone, PW, Braccia, D, Larson, E. Systematic review of economic analyses of health care-associated infections. Am J Infect Control 2005;33:501509.CrossRefGoogle ScholarPubMed
7. Shannon, RP, Patel, B, Cummins, D, Shannon, AH, Ganguli, G, Lu, Y. Economics of central line–associated bloodstream infections. Am J Med Qual 2006;21:7S16S.CrossRefGoogle ScholarPubMed
8. Warren, DK, Quadir, WW, Hollenbeak, CS, Elward, AM, Cox, MJ, Fraser, VJ. Attributable cost of catheter-associated bloodstream infections among intensive care patients in a nonteaching hospital. Crit Care Med 2006;34:20842089.CrossRefGoogle Scholar
9. Ashton, CM, Kuykendall, DH, Johnson, ML, Wray, NP, Wu, L. The association between the quality of inpatient care and early readmission. Ann Intern Med 1995;122:415421.CrossRefGoogle ScholarPubMed
10. Jencks, SF, Williams, MV, Coleman, EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med 2009;360:14181428.CrossRefGoogle ScholarPubMed
11. Hasan, M. Readmission of patients to hospital: still ill defined and poorly understood. Int J Qual Health Care 2001;13:177179.CrossRefGoogle ScholarPubMed
12. Tierney, AJ, Worth, A. Review: readmission of elderly patients to hospital. Age Ageing 1995;24:163166.CrossRefGoogle ScholarPubMed
13. Victor, CR, Vetter, NJ. The early readmission of the elderly to hospital. Age Ageing 1985;14:3742.CrossRefGoogle ScholarPubMed
14. Williams, EI, Fitton, F. Factors affecting early unplanned readmission of elderly patients to hospital. BMJ 1988;297:784787.CrossRefGoogle ScholarPubMed
15. Thomas, JW, Holloway, JJ. Investigating early readmission as an indicator for quality of care studies. Med Care 1991;29:377394.CrossRefGoogle ScholarPubMed
16. Weinberger, M, Oddone, EZ, Henderson, WG. Does increased access to primary care reduce hospital readmissions? Veterans Affairs Cooperative Study Group on Primary Care and Hospital Readmission. N Engl J Med 1996;334:14411447.CrossRefGoogle Scholar
17. Sreeramoju, P, Montie, B, Ramirez, AM, Ayeni, A. Healthcare-associated infection: a significant cause of hospital readmission. Infect Control Hosp Epidemiol 2010;31:11951197.CrossRefGoogle ScholarPubMed
18. Sherman, ER, Heydon, KH, St John, KH, et al. Administrative data fail to accurately identify cases of healthcare-associated infection. Infect Control Hosp Epidemiol 2006;27:332337.CrossRefGoogle ScholarPubMed
19. Malpiedi, PJ, Peterson, KD, Soe, MM, et al. 2011 National and State Healthcare-Associated Infection Standardized Infection Ratio Report. Atlanta, GA: Centers for Disease Control and Prevention, 2013.Google Scholar
20. Baggs, JM, Scott, RD II, Wise, ME, et al. Determining attributable Medicare reimbursement for central line associated bloodstream infections (CLABSI) reported to the National Healthcare Safety Network (NHSN). In: Program and abstracts of the Inaugural Annual Scientific Meeting of IDWeek; October 17–21, 2012; San Diego, CA. Abstract 893.Google Scholar
21. Yi, SH, Baggs, J, Gould, CV, Scott, RD 2nd, Jernigan, JA. Medicare reimbursement attributable to catheter-associated urinary tract infection in the inpatient setting: a retrospective cohort analysis. Med Care 2014;52:469478.CrossRefGoogle ScholarPubMed
22. Centers for Disease Control and Prevention. Bloodstream infection event (central line-associated bloodstream infection and non-central line-associated bloodstream infection). http://www.cdc.gov/nhsn/pdfs/pscmanual/4psc_clabscurrent.pdf. 2015.Google Scholar
23. Social Security Administration. Medicare. http://www.socialsecurity.gov/pubs/10043.html#a0=2. 2014.Google Scholar
24. Agency for Healthcare Research and Quality. Clinical Classifications Software (ICD-9-CM) [computer program]. http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Rockville, MD: Agency for Healthcare Research and Quality, 2015.Google Scholar
25. Gagne, JJ, Glynn, RJ, Avorn, J, Levin, R, Schneeweiss, S. A combined comorbidity score predicted mortality in elderly patients better than existing scores. J Clin Epidemiol 2011;64:749759.CrossRefGoogle ScholarPubMed
26. Kleinbaum, DG, Klein, M. Logistic Regression: A Self-Learning Text, 2nd ed. New York: Springer, 2002.Google Scholar
27. Emerson, CB, Eyzaguirre, LM, Albrecht, JS, Comer, AC, Harris, AD, Furuno, JP. Healthcare-associated infection and hospital readmission. Infect Control Hosp Epidemiol 2012;33:539544.CrossRefGoogle ScholarPubMed
28. Mattner, F, Biertz, F, Ziesing, S, Gastmeier, P, Chaberny, IF. Long-term persistence of MRSA in re-admitted patients. Infection 2010;38:363371.CrossRefGoogle ScholarPubMed
29. Murphy, CR, Avery, TR, Dubberke, ER, Huang, SS. Frequent hospital readmissions for Clostridium difficile infection and the impact on estimates of hospital-associated C. difficile burden. Infect Control Hosp Epidemiol 2012;33:2028.CrossRefGoogle ScholarPubMed
30. Kaboli, PJ, Go, JT, Hockenberry, J, et al. Associations between reduced hospital length of stay and 30-day readmission rate and mortality: 14-year experience in 129 Veterans Affairs hospitals. Ann Intern Med 2012;157:837845.CrossRefGoogle ScholarPubMed
31. Goto, M, Ohl, ME, Schweizer, ML, Perencevich, EN. Accuracy of administrative code data for the surveillance of healthcare-associated infections: a systematic review and meta-analysis. Clin Infect Dis 2014;58:688696.CrossRefGoogle ScholarPubMed
32. van Walraven, C, Austin, P. Administrative database research has unique characteristics that can risk biased results. J Clin Epidemiol 2012;65:126131.CrossRefGoogle ScholarPubMed
33. Scott, RD 2nd, Sinkowitz-Cochran, R, Wise, ME, et al. CDC central-line bloodstream infection prevention efforts produced net benefits of at least $640 million during 1990-2008. Health Aff 2014;33:10401047.CrossRefGoogle ScholarPubMed
34. Dunagan, WC, Woodward, RS, Medoff, G, et al. Antimicrobial misuse in patients with positive blood cultures. Am J Med 1989;87:253259.CrossRefGoogle ScholarPubMed