Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-24T21:40:18.556Z Has data issue: false hasContentIssue false
  • English
  • Français

Healthcare-associated urinary tract infections with onset post hospital discharge

Published online by Cambridge University Press:  20 June 2019

Miriam R. Elman ,
Craig D. Williams ,
David T. Bearden ,
John M. Townes ,
John D. Heintzman ,
Jodi A. Lapidus ,
Ravina Kullar ,
Sheila Markwardt ,
Amanda T. Trieu  and
Arrash A. Vahidi
...Show all authors
Miriam R. Elman
Affiliation:
School of Public Health, Oregon Health and Science University–Portland State University, Portland, Oregon
Craig D. Williams
Affiliation:
Department of Pharmacy Practice, College of Pharmacy, Oregon State University/Oregon Health and Science University, Portland, Oregon
David T. Bearden
Affiliation:
Department of Pharmacy Practice, College of Pharmacy, Oregon State University/Oregon Health and Science University, Portland, Oregon
John M. Townes
Affiliation:
Division of Infectious Diseases, Department of Medicine, School of Medicine, Oregon Health and Science University, Portland, Oregon
John D. Heintzman
Affiliation:
Department of Family Medicine, School of Medicine, Oregon Health and Science University, Portland, Oregon
Jodi A. Lapidus
Affiliation:
School of Public Health, Oregon Health and Science University–Portland State University, Portland, Oregon
Ravina Kullar
Affiliation:
Doctor Evidence, Santa Monica, California
Sheila Markwardt
Affiliation:
School of Public Health, Oregon Health and Science University–Portland State University, Portland, Oregon
Amanda T. Trieu
Affiliation:
Kaiser Permanente, Portland, Oregon
Arrash A. Vahidi
Affiliation:
Department of Pharmacy Services, Veterans’ Affairs Portland Health Care System, Portland, Oregon
Jessina C. McGregor*
Affiliation:
School of Public Health, Oregon Health and Science University–Portland State University, Portland, Oregon Department of Pharmacy Practice, College of Pharmacy, Oregon State University/Oregon Health and Science University, Portland, Oregon
*
Author for correspondence: Jessina C. McGregor, PhD, OSU/OHSU College of Pharmacy, 2730 SW Moody Ave, CL5CP, Portland, OR 97201. Email: [email protected] Or Miriam R. Elman, MS, MPH, OHSU-PSU School of Public Health, 3181 SW Sam Jackson Park Rd, CB669, Portland, OR 97239. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

Current surveillance for healthcare-associated (HA) urinary tract infection (UTI) is focused on catheter-associated infection with hospital onset (HO-CAUTI), yet this surveillance does not represent the full burden of HA-UTI to patients. Our objective was to measure the incidence of potentially HA, community-onset (CO) UTI in a retrospective cohort of hospitalized patients.

Design:

Retrospective cohort study.

Setting:

Academic, quaternary care, referral center.

Patients:

Hospitalized adults at risk for HA-UTI from May 2009 to December 2011 were included.

Methods:

Patients who did not experience a UTI during the index hospitalization were followed for 30 days post discharge to identify cases of potentially HA-CO UTI.

Results:

We identified 3,273 patients at risk for potentially HA-CO UTI. The incidence of HA-CO UTI in the 30 days post discharge was 29.8 per 1,000 patients. Independent risk factors of HA-CO UTI included paraplegia or quadriplegia (adjusted odds ratio [aOR], 4.6; 95% confidence interval [CI], 1.2–18.0), indwelling catheter during index hospitalization (aOR, 1.5; 95% CI, 1.0–2.3), prior piperacillin-tazobactam prescription (aOR, 2.3; 95% CI, 1.1–4.5), prior penicillin class prescription (aOR, 1.7; 95% CI, 1.0–2.8), and private insurance (aOR, 0.6; 95% CI, 0.4–0.9).

Conclusions:

HA-CO UTI may be common within 30 days following hospital discharge. These data suggest that surveillance efforts may need to be expanded to capture the full burden to patients and better inform antibiotic prescribing decisions for patients with a history of hospitalization.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 40 , Issue 8 , August 2019 , pp. 863 - 871
Copyright
© 2019 by The Society for Healthcare Epidemiology of America. All rights reserved. 

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.)

Footnotes

PREVIOUS PRESENTATION: Portions of this work were previously presented at IDWeek 2013 on October 4, 2013, in San Francisco, California.

References

Klevens, RM, Edwards, JR, Richards, CL Jr, et al. Estimating health care-associated infections and deaths in US hospitals, 2002. Public Health Rept 2007;122:160–166.CrossRefGoogle Scholar
Magill, SS, Edwards, JR, Bamberg, W, et al. Multistate point-prevalence survey of health care-associated infections. N Engl J Med 2014;370:1198–1208.CrossRefGoogle ScholarPubMed
Magill, SS, Hellinger, W, Cohen, J, et al. Prevalence of healthcare-associated infections in acute care hospitals in Jacksonville, Florida. Infect Control Hosp Epidemiol 2012;33:283–291.CrossRefGoogle ScholarPubMed
National Heatlhcare Saftey Network. Urinary tract infection (catheter-associated urinary tract infection [CAUTI] and non-catheter-associated urinary tract infection [UTI]) and other urinary system infection [USI]) events. Centers for Disease Control and Prevention website. https://www.cdc.gov/nhsn/pdfs/pscmanual/7psccauticurrent.pdf. Published 2018. Accessed May 15, 2018.Google Scholar
Elixhauser, A, Steiner, C, Harris, DR, Coffey, RM. Comorbidity measures for use with administrative data. Med Care 1998;36:8–27.CrossRefGoogle ScholarPubMed
HCUP Comorbidity Software [computer program]. Version 3.7. Rockville, MD: Agency for Healthcare Research and Quality; 2015.Google Scholar
Thompson, NR, Fan, Y, Dalton, JE, et al. A new Elixhauser-based comorbidity summary measure to predict in-hospital mortality. Med Care 2015;53:374–379.CrossRefGoogle ScholarPubMed
Hart, G, Cromartie, J. Rural-urban commuting areas (RUCAs) geographic taxonomy. 3.10 ed. Center for Rural Health, University of North Dakota: Grand Forks, ND, 2014.Google Scholar
RUCA Data. Rural Health Research Center website. http://depts.washington.edu/uwruca/ruca-uses.php. Accessed November 10, 2015.Google Scholar
R: A Language and Environment for Statistical Computing [computer program]. Vienna, Austria: R Foundation for Statistical Computing; 2015.Google Scholar