Hostname: page-component-745bb68f8f-s22k5 Total loading time: 0 Render date: 2025-01-08T09:56:58.862Z Has data issue: false hasContentIssue false
  • English
  • Français

The Economic Value of the Centers for Disease Control and Prevention Carbapenem-Resistant Enterobacteriaceae Toolkit

Published online by Cambridge University Press:  19 March 2018

Sarah M. Bartsch ,
Susan S. Huang ,
James A. McKinnell ,
Kim F. Wong ,
Leslie E. Mueller ,
Loren G. Miller  and
Bruce Y. Lee
Sarah M. Bartsch
Affiliation:
Public Health Computational and Operations Research (PHICOR), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
Susan S. Huang
Affiliation:
Division of Infectious Diseases and Health Policy Research Institute, University of California Irvine Health School of Medicine, Irvine, California
James A. McKinnell
Affiliation:
Infectious Disease Clinical Outcomes Research Unit (ID-CORE), Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California Torrance Memorial Medical Center, Torrance, California
Kim F. Wong
Affiliation:
Center for Research Computing, University of Pittsburgh, Pittsburgh, Pennsylvania
Leslie E. Mueller
Affiliation:
Public Health Computational and Operations Research (PHICOR), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
Loren G. Miller
Affiliation:
Infectious Disease Clinical Outcomes Research Unit (ID-CORE), Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California
Bruce Y. Lee*
Affiliation:
Public Health Computational and Operations Research (PHICOR), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
*
Address correspondence to Bruce Y. Lee, MD, MBA, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Room W3501, Baltimore, MD 21205 ([email protected]).
Get access Rights & Permissions [Opens in a new window]

Abstract

OBJECTIVE

While previous work showed that the Centers for Disease Control and Prevention toolkit for carbapenem-resistant Enterobacteriaceae (CRE) can reduce spread regionally, these interventions are costly, and decisions makers want to know whether and when economic benefits occur.

DESIGN

Economic analysis

SETTING

Orange County, California

METHODS

Using our Regional Healthcare Ecosystem Analyst (RHEA)-generated agent-based model of all inpatient healthcare facilities, we simulated the implementation of the CRE toolkit (active screening of interfacility transfers) in different ways and estimated their economic impacts under various circumstances.

RESULTS

Compared to routine control measures, screening generated cost savings by year 1 when hospitals implemented screening after identifying ≤20 CRE cases (saving $2,000–$9,000) and by year 7 if all hospitals implemented in a regional coordinated manner after 1 hospital identified a CRE case (hospital perspective). Cost savings was achieved only if hospitals independently screened after identifying 10 cases (year 1, third-party payer perspective). Cost savings was achieved by year 1 if hospitals independently screened after identifying 1 CRE case and by year 3 if all hospitals coordinated and screened after 1 hospital identified 1 case (societal perspective). After a few years, all strategies cost less and have positive health effects compared to routine control measures; most strategies generate a positive cost-benefit each year.

CONCLUSIONS

Active screening of interfacility transfers garnered cost savings in year 1 of implementation when hospitals acted independently and by year 3 if all hospitals collectively implemented the toolkit in a coordinated manner. Despite taking longer to manifest, coordinated regional control resulted in greater savings over time.

Infect Control Hosp Epidemiol 2018;39:516–524

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 39 , Issue 5 , May 2018 , pp. 516 - 524
Copyright
© 2018 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.)

References

REFERENCES

1. Lee, BY, Bartsch, SM, Wong, KF, et al. The potential trajectory of carbapenem-resistant Enterobacteriaceae, an emerging threat to health-care facilities, and the impact of the Centers for Disease Control and Prevention toolkit. Am J Epidemiol 2016;183:471–479.Google Scholar
2. Slayton, RB, Toth, D, Lee, BY, et al. Vital signs: estimated effects of coordinated action to reduce antibiotic-resistant infections in health care facilities—United States. MMWR Morb Mortal Wkly Rep 2015;64:826–831.CrossRefGoogle ScholarPubMed
3. Centers for Disease Control and Prevention. Antibiotic resistance threats in the United States 2013. Atlanta, GA: Centers for Disease Control and Prevention; 2013.Google Scholar
4. Bartsch, SM, McKinnell, JA, Mueller, LE, et al. Potential economic burden of carbapenem-resistant Enterobacteriaceae (CRE) in the United States. Clin Microbiol Infect 2017;23:48.e9–e16.CrossRefGoogle ScholarPubMed
5. Lee, BY, Wong, KF, Bartsch, SM, et al. The Regional Healthcare Ecosystem Analyst (RHEA): simulation modeling tool to assist infectious disease control in a health system. J Am Med Informat Assoc 2013;20:e139–e146.CrossRefGoogle Scholar
6. Lee, BY, Bartsch, SM, Wong, KF, et al. Simulation shows hospitals that cooperate on infection control obtain better results than hospitals acting alone. Health Affairs 2012;31:2295–2303.CrossRefGoogle ScholarPubMed
7. Borer, A, Saidel-Odes, L, Eskira, S, et al. Risk factors for developing clinical infection with carbapenem-resistant Klebsiella pneumoniae in hospital patients initially only colonized with carbapenem-resistant K. pneumoniae . Am J Infect Control 2012;40:421–425.Google Scholar
8. Debby, BD, Ganor, O, Yasmin, M, et al. Epidemiology of carbapenem resistant Klebsiella pneumoniae colonization in an intensive care unit. Eur J Clin Microbiol Infect Dis 2012;31:1811–1817.Google Scholar
9. Falagas, ME, Tansarli, GS, Karageorgopoulos, DE, Vardakas, KZ. Deaths attributable to carbapenem-resistant Enterobacteriaceae infections. Emerg Infect Dis 2014;20:1170–1175.Google Scholar
10. Healthcare associated infections: tracking CRE, Atlanta, GA. Centers for Disease Control and Prevention website. http://www.cdc.gov/hai/organisms/cre/TrackingCRE.html. Published 2015. Updated November 2017. Accessed February 19, 2018.Google Scholar
11. Guh, AY, Limbago, B, Kallen, AJ. Epidmiology and prevention of carbapenem-resistant Enterobacteriaceae in the United States. Expert Rev Anti Infect Ther 2014;12:565–580.Google Scholar
12. Jacob, JT, Klein, E, Laxminarayan, R, et al. Vital signs: carbapenem-resistant Enterobacteriaceae . MMWR Morb Mortal Wkly Rep 2013;62:165–170.Google Scholar
13. Thaden, JT, Lewis, SS, Hazen, KC, et al. Rising rates of carbapenem-resistant Enterobacteriaceae in community hospitals: a mixed-method review of epidemology and microbiology practices in a network of community hospitals in the southeastern United States. Infect Control Hosp Epidemiol 2014;35:978–983.Google Scholar
14. Kim, J, Segreti, J, Tomich, A, Tongma, C, Hayden, MK, Lin, MY. editorsSurveillance and inter-facility communication for carbapenem-resistant Enterobacteriaceae (CRE). Society for Healthcare Epidemiology of America; 2016.Google Scholar
15. Lee, BY. Digital decision making: computer models and antibiotic prescribing in the twenty-first century. Clin Infect Dis 2008;46:1139–1141.Google Scholar
Supplementary material: File

Bartsch et al. supplementary material

Bartsch et al. supplementary material 1

Download Bartsch et al. supplementary material(File)
File 90.5 KB
Supplementary material: File

Bartsch et al. supplementary material

Bartsch et al. supplementary material 2

Download Bartsch et al. supplementary material(File)
File 94.6 KB