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Research Methods in Healthcare Epidemiology and Antimicrobial Stewardship—Quasi-Experimental Designs

Part of: Research and Methodology in Infection Control

Published online by Cambridge University Press:  07 June 2016

Marin L. Schweizer ,
Barbara I. Braun  and
Aaron M. Milstone
Marin L. Schweizer*
Affiliation:
Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City, Iowa Center for Comprehensive Access and Delivery Research and Evaluation, Iowa City VA Health Care System, Iowa City, Iowa
Barbara I. Braun
Affiliation:
Department of Health Services Research, The Joint Commission, Oakbrook Terrace, Illinois
Aaron M. Milstone
Affiliation:
Department of Pediatrics, Division of Pediatric Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland Department of Hospital Epidemiology and Infection Control, Johns Hopkins Hospital, Baltimore, Maryland
*
Address correspondence to Marin L. Schweizer, PhD, Iowa City VA Health Care System (152), 601 Hwy 6 West, Iowa City, IA 52246 ([email protected]).
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Abstract

Quasi-experimental studies evaluate the association between an intervention and an outcome using experiments in which the intervention is not randomly assigned. Quasi-experimental studies are often used to evaluate rapid responses to outbreaks or other patient safety problems requiring prompt, nonrandomized interventions. Quasi-experimental studies can be categorized into 3 major types: interrupted time-series designs, designs with control groups, and designs without control groups. This methods paper highlights key considerations for quasi-experimental studies in healthcare epidemiology and antimicrobial stewardship, including study design and analytic approaches to avoid selection bias and other common pitfalls of quasi-experimental studies.

Infect Control Hosp Epidemiol 2016;1–6

Type
SHEA White Papers
Information
Infection Control & Hospital Epidemiology , Volume 37 , Issue 10 , October 2016 , pp. 1135 - 1140
Copyright
© 2016 by The Society for Healthcare Epidemiology of America. All rights reserved 

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References

REFERENCES

1. Harris, AD, Bradham, DD, Baumgarten, M, Zuckerman, IH, Fink, JC, Perencevich, EN. The use and interpretation of quasi-experimental studies in infectious diseases. Clin Infect Dis 2004;38:1586–1591.Google ScholarPubMed
2. Shadish, WR, Cook, TD, Campbell, DT. Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Boston: Houghton Mifflin; 2002.Google Scholar
3. Grimshaw, J, Campbell, M, Eccles, M, Steen, N. Experimental and quasi-experimental designs for evaluating guideline implementation strategies. Fam Pract 2000;17:S11–S16.Google Scholar
4. Shardell, M, Harris, AD, El-Kamary, SS, Furuno, JP, Miller, RR, Perencevich, EN. Statistical analysis and application of quasi experiments to antimicrobial resistance intervention studies. Clin Infect Dis 2007;45:901–907.Google Scholar
5. Thorpe, KE, Zwarenstein, M, Oxman, AD, et al. A pragmatic-explanatory continuum indicator summary (PRECIS): a tool to help trial designers. J Clin Epidemiol 2009;62:464–475.Google Scholar
6. Lee, AS, Cooper, BS, Malhotra-Kumar, S, et al. Comparison of strategies to reduce meticillin-resistant Staphylococcus aureus rates in surgical patients: a controlled multicentre intervention trial. BMJ Open 2013;3:e003126.Google Scholar
7. Harris, AD, Lautenbach, E, Perencevich, E. A systematic review of quasi-experimental study designs in the fields of infection control and antibiotic resistance. Clin Infect Dis 2005;41:77–82.Google Scholar
8. Hill, AB. The environment and disease: association or causation? Proc R Soc Med 1965;58:295–300.Google Scholar
9. Crabtree, BF, Ray, SC, Schmidt, PM, O’Connor, PJ, Schmidt, DD. The individual over time: time series applications in health care research. J Clin Epidemiol 1990;43:241–260.Google Scholar
10. Des Jarlais, DC, Lyles, C, Crepaz, N. Improving the reporting quality of nonrandomized evaluations of behavioral and public health interventions: the TREND statement. Am J Public Health 2004;94:361–366.Google Scholar
11. Schweizer, ML, Chiang, HY, Septimus, E, et al. Association of a bundled intervention with surgical site infections among patients undergoing cardiac, hip, or knee surgery. JAMA 2015;313:2162–2171.CrossRefGoogle ScholarPubMed
12. Quach, C, Milstone, AM, Perpete, C, Bonenfant, M, Moore, DL, Perreault, T. Chlorhexidine bathing in a tertiary care neonatal intensive care unit: impact on central line-associated bloodstream infections. Infect Control Hosp Epidemiol 2014;35:158–163.CrossRefGoogle Scholar
13. Yin, J, Schweizer, ML, Herwaldt, LA, Pottinger, JM, Perencevich, EN. Benefits of universal gloving on hospital-acquired infections in acute care pediatric units. Pediatrics 2013;131:e1515–e1520.CrossRefGoogle ScholarPubMed
14. Popoola, VO, Colantuoni, E, Suwantarat, N, et al. Active surveillance cultures and decolonization to reduce Staphylococcus aureus infections in the neonatal intensive care unit. Infect Control Hosp Epidemiol 2016;37:381–387.Google Scholar
15. Waters, TM, Daniels, MJ, Bazzoli, GJ, et al. Effect of Medicare’s nonpayment for hospital-acquired conditions: lessons for future policy. JAMA Intern Med 2015;175:347–354.Google Scholar
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