Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-17T14:09:40.052Z Has data issue: false hasContentIssue false

Quasi-experimental Studies in the Fields of Infection Control and Antibiotic Resistance, Ten Years Later: A Systematic Review

Published online by Cambridge University Press:  08 February 2018

Rotana Alsaggaf
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Lyndsay M. O’Hara
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Kristen A. Stafford
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Surbhi Leekha
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Anthony D. Harris*
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
*
Address correspondence to Anthony D. Harris, MD, MPH, 685 W Baltimore St, MSTF 330, Baltimore, MD 21201 ([email protected]).

Abstract

OBJECTIVE

A systematic review of quasi-experimental studies in the field of infectious diseases was published in 2005. The aim of this study was to assess improvements in the design and reporting of quasi-experiments 10 years after the initial review. We also aimed to report the statistical methods used to analyze quasi-experimental data.

DESIGN

Systematic review of articles published from January 1, 2013, to December 31, 2014, in 4 major infectious disease journals.

METHODS

Quasi-experimental studies focused on infection control and antibiotic resistance were identified and classified based on 4 criteria: (1) type of quasi-experimental design used, (2) justification of the use of the design, (3) use of correct nomenclature to describe the design, and (4) statistical methods used.

RESULTS

Of 2,600 articles, 173 (7%) featured a quasi-experimental design, compared to 73 of 2,320 articles (3%) in the previous review (P<.01). Moreover, 21 articles (12%) utilized a study design with a control group; 6 (3.5%) justified the use of a quasi-experimental design; and 68 (39%) identified their design using the correct nomenclature. In addition, 2-group statistical tests were used in 75 studies (43%); 58 studies (34%) used standard regression analysis; 18 (10%) used segmented regression analysis; 7 (4%) used standard time-series analysis; 5 (3%) used segmented time-series analysis; and 10 (6%) did not utilize statistical methods for comparisons.

CONCLUSIONS

While some progress occurred over the decade, it is crucial to continue improving the design and reporting of quasi-experimental studies in the fields of infection control and antibiotic resistance to better evaluate the effectiveness of important interventions.

Infect Control Hosp Epidemiol 2018;39:170–176

Type
Original Articles
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. Shadish, WR, Cook, TD, Campbel, DT. Experimental and Quasi-experimental Designs for Generalized Causal Inference. Boston: Houghton Mifflin; 2002.Google Scholar
2. 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;45:901907.Google Scholar
3. 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;38:15861591.Google ScholarPubMed
4. Morgan, GA, Gliner, JA, Harmon, RJ. Quasi-experimental designs. J Am Acad Child Adolesc Psychiatry 2000;39:794796.Google Scholar
5. Schweizer, ML, Braun, BI, Milstone, AM. Research methods in healthcare epidemiology and antimicrobial stewardship-quasi-experimental designs. Infect Control Hosp Epidemiol 2016;37:11351140.Google Scholar
6. 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;41:7782.Google Scholar
7. Schulz, KF, Altman, DG, Moher, D, Group, C. Consort 2010 statement: updated guidelines for reporting parallel group randomized trials. Ann Intern Med 2010;152:726732.CrossRefGoogle ScholarPubMed
8. von Elm, E, Altman, DG, Egger, M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Int J Surg 2014;12:14951499.CrossRefGoogle ScholarPubMed
9. Moher, D, Liberati, A, Tetzlaff, J, Altman, DG, Group, P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg 2010;8:336341.CrossRefGoogle ScholarPubMed
10. Stone, SP, Cooper, BS, Kibbler, CC, et al. The ORION statement: guidelines for transparent reporting of outbreak reports and intervention studies of nosocomial infection. Lancet Infect Dis 2007;7:282288.Google Scholar
11. Des Jarlais, DC, Lyles, C, Crepaz, N, Group, T. Improving the reporting quality of nonrandomized evaluations of behavioral and public health interventions: the TREND statement. Am J Public Health 2004;94:361366.Google Scholar
12. Moher, D, Liberati, A, Tetzlaff, J, Altman, DG , The PRISMA Group (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 6(7):e1000097. doi: 10.1371/journal.pmed1000097.CrossRefGoogle ScholarPubMed
Supplementary material: File

Alsaggaf et al. supplementary material

Alsaggaf et al. supplementary material 1

Download Alsaggaf et al. supplementary material(File)
File 219 KB