Hostname: page-component-8448b6f56d-tj2md Total loading time: 0 Render date: 2024-04-23T07:48:05.236Z Has data issue: false hasContentIssue false
  • English
  • Français

Epidemiology and Healthcare Costs of Incident Clostridium difficile Infections Identified in the Outpatient Healthcare Setting

Published online by Cambridge University Press:  02 January 2015

Jennifer L. Kuntz ,
Eric S. Johnson ,
Marsha A. Raebel ,
Amanda F. Petrik ,
Xiuhai Yang ,
Micah L. Thorp ,
Steven J. Spindel ,
Nancy Neil  and
David H. Smith
Jennifer L. Kuntz*
Affiliation:
Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
Eric S. Johnson
Affiliation:
Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
Marsha A. Raebel
Affiliation:
Institute for Health Research, Kaiser Permanente Colorado, Denver, Colorado University of Colorado School of Pharmacy, Denver, Colorado
Amanda F. Petrik
Affiliation:
Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
Xiuhai Yang
Affiliation:
Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
Micah L. Thorp
Affiliation:
Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
Steven J. Spindel
Affiliation:
Department of Infectious Diseases, Kaiser Permanente Northwest, Portland, Oregon
Nancy Neil
Affiliation:
Decision Research, Eugene, Oregon University of Washington, Seattle, Washington
David H. Smith
Affiliation:
Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
*
Center for Health Research, Kaiser Permanente Northwest, 3800 North Interstate Avenue, Portland, OR 97227 (jennifer.l.kuntz@kpchr.org)
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective.

To describe the epidemiology and healthcare costs of Clostridium difficile infection (CDI) identified in the outpatient setting.

Design.

Population-based, retrospective cohort study.

Patients.

Kaiser Permanente Colorado and Kaiser Permanente Northwest members between June 1, 2005, and September 30, 2008.

Methods.

We identified persons with incident CDI and classified CDI by whether it was identified in the outpatient or inpatient healthcare setting. We collected information about baseline variables and follow-up healthcare utilization, costs, and outcomes among patients with CDI. We compared characteristics of patients with CDI identified in the outpatient versus inpatient setting.

Results.

We identified 3,067 incident CDIs; 56% were identified in the outpatient setting. Few strong, independent predictors of diagnostic setting were identified, although a previous stay in a nonacute healthcare institution (odds ratio [OR], 1.45 [95% confidence interval (CI), 1.13-1.86]) was statistically associated with outpatient-identified CDI, as was age from 50 to 59 years (OR, 1.64 [95% CI, 1.18-2.29]), 60 to 69 years (OR, 1.37 [95% CI, 1.03-1.82]), and 70 to 79 years (OR, 1.36 [95% CI, 1.06-1.74]), when compared with persons aged 80-89 years.

Conclusions.

We found that more than one-half of incident CDIs in this population were identified in the outpatient setting. Patients with outpatient-identified CDI were younger with fewer comorbidities, although they frequently had previous exposure to healthcare. These data suggest that practitioners should be aware of CDI and obtain appropriate diagnostic testing on outpatients with CDI symptoms.

Infect Control Hosp Epidemiol 2012;33(10):1031-1038

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 33 , Issue 10 , October 2012 , pp. 1031 - 1038
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Elixhauser, A, Jhung, M. Clostridium difficile-Associated Disease in U.S. Hospitals, 1993–2005. Statistical brief 50. Rockville, MD: Healthcare Cost and Utilization Project, 2006.Google ScholarPubMed
2.Gerding, DN, Johnson, S, Peterson, LR, Mulligan, ME, Silva, J Jr. Clostridium difficile-associated diarrhea and colitis. Infect Control Hosp Epidemiol 1995;16:459–477.CrossRefGoogle ScholarPubMed
3.Bignardi, GE. Risk factors for Clostridium difficile infection. J Hosp Infect 1998;40:1–15.Google Scholar
4.Blondeau, JM. What have we learned about antimicrobial use and the risks for Clostridium difficile-associated diarrhoea? J Antimicrob Chemother 2009;63:238–242.Google Scholar
5.Kuntz, JL, Chrischilles, EA, Pendergast, JF, Herwaldt, LA, Polgreen, PM. Incidence of and risk factors for community-associated Clostridium difficile infection: a nested case-control study. BMC Infect Dis 2011;11:194.CrossRefGoogle ScholarPubMed
6.Hirshon, JM, Thompson, AD, Limbago, B, et al.Clostridium difficile infection in outpatients, Maryland and Connecticut, USA, 2002–2007. Emerg Infect Dis 2011;17:1946–1949.Google Scholar
7.Fellmeth, G, Yarlagadda, S, Iyer, S. Epidemiology of community-onset Clostridium difficile infection in a community in the south of England. J Infect Public Health 2010;3:118–123.Google Scholar
8.Bauer, MP, Goorhuis, A, Koster, T, et al.Community-onset Clostridium difficile-associated diarrhoea not associated with antibiotic usage: two case reports with review of the changing epidemiology of Clostridium difficile-associated diarrhoea. Neth J Med 2008;66:207–211.Google Scholar
9.Centers for Disease Control and Prevention. Surveillance for community-associated Clostridium difficile. Connecticut, 2006. MMWR Morb Mortal Wkly Rep 2008;57:340–343.Google Scholar
10.Centers for Disease Control and Prevention. Severe Clostridium difficile-associated disease in populations previously at low risk: four states, 2005. MMWR Morb Mortal Wkly Rep 2005;54:1201–1205.Google Scholar
11.Hirschhorn, LR, Trnka, Y, Onderdonk, A, Lee, ML, Platt, R. Epidemiology of community-acquired Clostridium difficile-associated diarrhea. J Infect Dis 1994;169:127–133.Google Scholar
12.McDonald, LC, Coignard, B, Dubberke, E, et al.Recommendations for surveillance of Clostridium difficile-associated disease. Infect Control Hosp Epidemiol 2007;28:140–145.Google Scholar
13.Dubberke, ER, Reske, KA, McDonald, LC, Fraser, VJ. ICD-9 codes and surveillance for Clostridium difficile-associated disease. Emerg Infect Dis 2006;12:1576–1579.Google Scholar
14.Scheurer, DB, Hicks, LS, Cook, EF, Schnipper, JL. Accuracy of ICD-9 coding for Clostridium difficile infections: a retrospective cohort. Epidemiol Infect 2007;135:1010–1013.Google Scholar
15.Levey, AS, Coresh, J, Balk, E, et al.National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann Intern Med 2003;139:137–147.Google Scholar
16.Harrell, FE. Regression Modeling Strategies. New York: Springer, 2001.CrossRefGoogle Scholar
17.Hornbrook, M, Goodman, MJ. Adjusting health benefit contributions to reflect risks. In: Hornbrook, M, ed. Risk Based Contributions to Private Health Insurance. Greenwich, CT: JAI, 1991: 41.Google Scholar
18.Palmore, TN, Sohn, S, Malak, SF, Eagan, J, Sepkowitz, KA. Risk factors for acquisition of Clostridium difficile-associated diarrhea among outpatients at a cancer hospital. Infect Control Hosp Epidemiol 2005;26:680–684.CrossRefGoogle Scholar
19.Dubberke, ER, Reske, KA, Olsen, MA, McDonald, LC, Fraser, VJ. Short- and long-term attributable costs of Clostridium difficile-associated disease in nonsurgical inpatients. Clin Infect Dis 2008;46:497–504.Google Scholar