862 infection control & hospital epidemiology july 2017, vol. 38, no. 7 One application of this method may be to identify a


hospital’s or unit’s adherence to antimicrobial stewardship policies over time and to provide trigger points for further ASP review. Trigger points would be those that were above (ie, potential overutilization due to inappropriate use) or below (ie, potential underutilization due to overly aggressive policy application) the prediction interval. In Figure 1, these trigger points are circled (ie, 3 below and 3 above the prediction interval). The stewardship team can conduct a drug utilization review for the antibiotic in question, focusing on the period surrounding the trigger point and determining whether use during the identified period was appropriate or inappropriate. Another application would be to test whether newly implemented stewardship strategies resulted in a departure from the previous linear trend (ie, Does consumption decrease beyond a certain prediction interval post implementation of stewardship strategy?). To measure impact, using the supplemental file, one would input the previous data that defined the past trend and would then omit data for the period that defined the intervention. The supplementary file is set up to automatically predict future trends. The investigator can utilize these calculations to determine whether the intervention resulted in a departure from the predicted trend. We have adapted a methodology to identify potential anti-


biotic outbreaks using a widely available program, Microsoft Excel. This method can be easily implemented in individual institutions using NHSN or other similarly collected antibiotic consumption data. Variation of site-specific antimicrobial consumption and internal trends in antimicrobial use can then be identified. Determining such trends is highly relevant for individual institutions and may provide antimicrobial stewardship programs a stable method for comparing antimicrobial consumption over time for conserved patient mixes (eg, their own hospital). We believe this method has a variety of applications including quality assessment of stewardship protocols, formulary changes, or drug shortages. It is important to understand several caveats when applying


this methodology. As with most mathematic models, predictions have inherent uncertainty. Thus, we advise caution when interpreting these data to avoid any overconfidence or confirmation bias. In addition, this method assumes linearity of predicted consumption values and homoscedasticity of errors. These assumptions can be easily confirmed or refuted through visual inspection, where predictions around the line at zero should have roughly equal numbers of residuals above and below zero. Once these assumptions are verified, this model can be applied as a practical screening tool to identify institution-specific utilization trends and consump- tion triggers for further investigation.


supplementary material


To view supplementary material for this article, please visit https://doi.org/10.1017/ice.2017.72


acknowledgments Financial support: No financial support was provided relevant to this article. Potential conflicts of interest: All authors report no conflicts of interest rele-


vant to this article. Affiliations: 1. Department of Pharmacy Practice, Midwestern University


Chicago College of Pharmacy, Downers Grove, Illinois; 2. Department of Pharmacy, Northwestern Memorial Hospital, Chicago, Illinois; 3. Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, Illinois; 4. Division of Pulmonary Critical Care, Northwestern University Feinberg School of Medicine, Chicago, Illinois. Address correspondence to Marc H. Scheetz, PharmD, MSc, Associate Professor of Pharmacy Practice, Midwestern University Chicago College of Pharmacy; 555 31st St, Downers Grove, IL 60515 (mschee@midwestern.edu).


Received November 25, 2016; accepted March 7, 2017; electronically published May 3, 2017 © 2017 by The Society for Healthcare Epidemiology of America. All rights reserved. 0899-823X/2017/3807-0014. DOI: 10.1017/ice.2017.72


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