Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012 Dec;140(12):2131-41.
doi: 10.1017/S0950268812000179. Epub 2012 Feb 16.

Modelling interrupted time series to evaluate prevention and control of infection in healthcare

V Gebski  1 , K Ellingson, J Edwards, J Jernigan, D Kleinbaum
Affiliations

Modelling interrupted time series to evaluate prevention and control of infection in healthcare

V Gebski et al. Epidemiol Infect. 2012 Dec.

Abstract

The most common methods for evaluating interventions to reduce the rate of new Staphylococcus aureus (MRSA) infections in hospitals use segmented regression or interrupted time-series analysis. We describe approaches to evaluating interventions introduced in different healthcare units at different times. We compare fitting a segmented Poisson regression in each hospital unit with pooling the individual estimates by inverse variance. An extension of this approach to accommodate potential heterogeneity allows estimates to be calculated from a single statistical model: a 'stacked' model. It can be used to ascertain whether transmission rates before the intervention have the same slope in all units, whether the immediate impact of the intervention is the same in all units, and whether transmission rates have the same slope after the intervention. The methods are illustrated by analyses of data from a study at a Veterans Affairs hospital. Both approaches yielded consistent results. Where feasible, a model adjusting for the unit effect should be fitted, or if there is heterogeneity, an analysis incorporating a random effect for units may be appropriate.

PubMed Disclaimer

Figures

Fig. 1.
Fig. 1.
Observed incident MRSA cases per 1000 patient-days. (a) Unit A, (b) unit B, and (c) area C.
Fig. 2.
Fig. 2.
Representation of model 1: within an individual unit. β0 = Starting baseline MRSA rate; β1 = slope of line prior to t0; β2 = drop at t0; β1 + β3 = slope after t0.
Fig. 3.
Fig. 3.
Representation of stacked data in model 2. ln(λ) = β0 + β1T + β2I + β3T* + γ1U2 + γ2U3; β1 = slope of line prior to intervention for units A, B, and area C; β2 = average drop at the intervention (drop occurs at T = 25 for unit A, T = 49 for unit B, T = 70 for area C; β1 + β3 = slope after intervention for units A, B, and area C. If β3 = 0, then the slopes are the same (β1) both before and after the intervention for all three units.
Fig. 4.
Fig. 4.
Representation of a model with a post-intervention threshold. ln(λ) = β0 + β1T + β2I +β3T* + β4T†.
See this image and copyright information in PMC

References

    1. Klevens R, et al. Invasive methicillin-resistant Staphylococcus aureus infections in the United States. Journal of the American Medical Association 2007. 298: 1763–1771. - PubMed
    1. Ellingson K, et al. Sustained reduction in the clinical incidence of methicillin-resistant Staphylococcus aureus colonization or infection associated with a multifaceted infection control intervention. Infection Control and Hospital Epidemiology 2011. 32: 1–8. - PubMed
    1. Brown C, Lilford R. The stepped wedge trial design: a systematic review. BMC Medical Research Methodology 2006; 6: 54. - PMC - PubMed
    1. Smith P. Splines as a useful and convenient statistical tool. American Statistician 1979; 33: 57–62.
    1. Kim H, et al. Comparability of segmented line regression models. Biometrics 2004; 60: 1005–1014. - PubMed

MeSH terms