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Monitoring Hand Hygiene via Human Observers: How Should We Be Sampling?
Jason Fries BA, Alberto M. Segre PhD, Geb Thomas PhD, Ted Herman PhD, Katherine Ellingson PhD and Philip M. Polgreen MD
Infection Control and Hospital Epidemiology
Vol. 33, No. 7 (July 2012), pp. 689-695
Published by: Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America
Stable URL: http://www.jstor.org/stable/10.1086/666346
Page Count: 7
You can always find the topics here!Topics: Health care industry, Simulations, Observational research, Intensive care units, Nurses, Perceptual localization, Standard deviation, Travel time, Medical practice, Securities and Exchange Commission regulation
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Objective. To explore how hand hygiene observer scheduling influences the number of events and unique individuals observed.Design. We deployed a mobile sensor network to capture detailed movement data for 6 categories of healthcare workers over a 2-week period.Setting. University of Iowa Hospital and Clinic medical intensive care unit (ICU).Methods. We recorded 33,721 time-stamped healthcare worker entries to and exits from patient rooms and considered each entry or exit to be an opportunity for hand hygiene. Architectural drawings were used to derive 4 optimal line-of-sight placements for observers. We ran simulations for different observer movement schedules, all with a budget of 1 hour of total observation time. We considered observation times of 1–15, 15–30, 30, and 60 minutes per station. We stochastically generated healthcare worker hand hygiene compliance on the basis of all data and recorded the total unit compliance as it would be reported by each simulated observer.Results. Considering a 60-minute total observation period, aggregate simulated observers captured 1.7% of the average total number of opportunities per day at best and 0.5% at worst. The 1–15-minute schedule captures, on average, 16% fewer events than does the 60-minute (ie, static) schedule, but it samples 17% more unique individuals. The 1–15-minute schedule also provides the best estimator of compliance for the duration of the shift, with a mean standard deviation of 17%, compared with 23% for the 60-minute schedule.Conclusions. Our results show that observations are sensitive to different observers’ schedules and suggest the importance of using data-driven approaches to schedule hand hygiene audits.
© 2012 by The Society for Healthcare Epidemiology of America. All rights reserved.