Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-22T06:17:15.820Z Has data issue: false hasContentIssue false

Substantial Variation in Hospital Rankings after Adjusting for Hospital-Level Predictors of Publicly-Reported Hospital-Associated Clostridium difficile Infection Rates

Published online by Cambridge University Press:  13 January 2015

Rupak Datta*
Affiliation:
Division of Infectious Diseases, University of California Irvine Medical Center, Orange, California Health Policy Research Institute, University of California Irvine School of Medicine, Irvine, California
N. Neely Kazerouni
Affiliation:
Center for Healthcare Quality, California Department of Public Health, Richmond, California
Jon Rosenberg
Affiliation:
Center for Healthcare Quality, California Department of Public Health, Richmond, California
Vinh Q. Nguyen
Affiliation:
Department of Statistics, University of California Irvine, Irvine, California.
Michael Phelan
Affiliation:
Department of Statistics, University of California Irvine, Irvine, California.
John Billimek
Affiliation:
Health Policy Research Institute, University of California Irvine School of Medicine, Irvine, California
Chenghua Cao
Affiliation:
Division of Infectious Diseases, University of California Irvine Medical Center, Orange, California Health Policy Research Institute, University of California Irvine School of Medicine, Irvine, California
Patricia McLendon
Affiliation:
Center for Healthcare Quality, California Department of Public Health, Richmond, California
Kate Cummings
Affiliation:
Center for Healthcare Quality, California Department of Public Health, Richmond, California
Susan S. Huang
Affiliation:
Division of Infectious Diseases, University of California Irvine Medical Center, Orange, California Health Policy Research Institute, University of California Irvine School of Medicine, Irvine, California
*
Address correspondence to Rupak Datta, MD, PhD, University of California Irvine School of Medicine, Health Policy Research Institute, 100 Theory, Suite 110, Irvine, CA 92697 ([email protected]).

Abstract

Across 366 California hospitals, we identified hospital-level characteristics predicting increased hospital-associated Clostridium difficile infection (HA-CDI) rates including more licensed beds, teaching and long-term acute care (LTAC) hospitals, and polymerase chain reaction testing. Adjustment for these characteristics impacted rankings in 24% of teaching hospitals, 13% of community hospitals, and 11% of LTAC hospitals.

Infect Control Hosp Epidemiol 2015;00(0): 1–3

Type
Concise Communications
Copyright
© 2015 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 PRESENTATIONS: Preliminary findings of this study were presented at IDWeek 2012 in San Diego, California, (October 17–21, 2012) on October 18, 2012 (Abstract 36359, Poster Board #350, Session #52 on C. difficile Epidemiology) and the 2013 Counsel of State and Territorial Epidemiologists Annual Conference in Pasadena, California (June 9–13, 2013) on June 12, 2013 (Abstract 2427, Session: Late-Breaker Abstracts).

References

REFERENCES

1. Magill, SS, Edwards, JR, Bamberg, W, et al. Multistate point-prevalence survey of healthcare-associated infections. N Engl J Med 2014;370:11981208.Google Scholar
2. Kachrimanidou, M, Malisiovas, N. Clostridium difficile infection: a comprehensive review. Crit Rev Microbiol 2011;37:178187.Google Scholar
3. Centers for Disease Control and Prevention. First state-specific healthcare-associated infections summary data report. CDC’s National healthcare safety network http://www.cdc.gov/hai/pdfs/stateplans/SIR_05_25_2010.pdf. Published 2010. Accessed November 25, 2014.Google Scholar
4. Ricciardi, R, Harriman, K, Baxter, NN, Hartman, LK, Town, RJ, Virnig, BA. Predictors of Clostridium difficile colitis infections in hospitals. Epidemiol Infect 2008;136:913921.Google Scholar
5. Office of Statewide Health Planning and Development. Healthcare Information Division. http://www.oshpd.ca.gov/HID/Products/PatDischargeData/PublicDataSet/. Published 2014. Accessed November 25, 2014.Google Scholar
6. Tehrani, DM, Phelan, MJ, Cao, C, et al. Substantial shifts in ranking of California hospitals by hospital-associated methicillin-resistant Staphylococcus aureus infection following adjustment for hospital characteristics and case mix. Infect Control Hosp Epidemiol 2014;35:12631270.Google Scholar
7. Donnelly, JP, Baddley, JW, Wang, HE. Antibiotic utilization for acute respiratory tract infections in US emergency departments. Antimicrob Agents Chemother 2014;58:14511457.Google Scholar
8. Polgreen, PM, Yang, M, Bohnett, LC, Cavanaugh, JE. A time-series analysis of Clostridium difficile and its seasonal association with influenza. Infect Control Hosp Epidemiol 2010;31:382387.Google Scholar
9. Romano, PS, Roos, LL, Jollis, JG. Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol 1993;46:10751079.Google Scholar
10. The National Healthcare Safety Network. Surveillance for C. difficile, MRSA, and other drug-resistant infections. Multidrug-resistant organism and Clostridium difficile infection (MDRO/CDI) module protocol. http://www.cdc.gov/nhsn/PDFs/pscManual/12pscMDRO_CDADcurrent.pdf. Published 2014. Accessed November 25, 2014.Google Scholar
11. Lee, Y, Nelder, JA, Pawitan, Y. Generalized linear models with random effects. London: CRC Press, 2006.Google Scholar
12. Zhang, Y, Steinman, MA, Kaplan, CM. Geographic variation in outpatient antibiotic prescribing among older adults. Arch Intern Med 2012;172:14651471.Google Scholar
13. Eng, JV, Marcus, R, Hadler, JL, et al. Consumer attitudes and use of antibiotics. Emerg Infect Dis 2003;9:11281135.Google Scholar