Center for Biofilm Engineering (CBE)
Permanent URI for this communityhttps://scholarworks.montana.edu/handle/1/9334
At the Center for Biofilm Engineering (CBE), multidisciplinary research teams develop beneficial uses for microbial biofilms and find solutions to industrially relevant biofilm problems. The CBE was established at Montana State University, Bozeman, in 1990 as a National Science Foundation Engineering Research Center. As part of the MSU College of Engineering, the CBE gives students a chance to get a head start on their careers by working on research teams led by world-recognized leaders in the biofilm field.
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Item Hand hygiene product use by food employees in casual dining and quick-service restaurants(Elsevier BV, 2023-02) Manuel, Clyde S.; Robbins, Greg; Slater, Jason; Walker, Diane K.; Parker, Albert; Arbogast, James W.Hand hygiene product usage characteristics by food employees when hand sanitizers are made available are not well understood. To investigate hand hygiene product usage in casual dining and quick-service restaurants, we placed automated monitoring soap and sanitizer dispensers side-by-side at handwash sinks used by food employees in seven restaurants. Dispenses were monitored, and multiple dispenses that occurred within 60 s of each other were considered a single hand hygiene event. This resulted in 186,998 events during the study (149,779 soap only, 21 985 sanitizer only, and 15,234 regimen [defined as soap followed by sanitizer at the same sink within 60 s]) over 15,447 days of use. Soap was the most frequently used hand hygiene method by food employees in both restaurant types. Regimen use, despite being the preferred hand hygiene method by both restaurant chains, was the least used hand hygiene method. When pooled over restaurant types, the median daily usage for soap was statistically significantly highest of all methods at 23.5 dispenses per sink per day (p < 0.0001), the sanitizer median daily usage was 4.27 dispenses per sink per day, and regimen use was statistically significantly lowest of all methods at 4.02 dispenses per sink per day (p < 0.0001). When hand hygiene event types were pooled, casual dining restaurants had similar median hand hygiene event rates (11.4 dispenses per sink per day) compared to quick-service restaurants (11.9 dispenses per sink per day; p = 0.890). The number of events by sink location varied, with sinks located at a warewash station having the highest number of events (19.3 dispenses per sink per day; p < 0.0001), while sinks located by a ready-to-eat food preparation area had the lowest number of events (6.8 dispenses per sink per day; p < 0.0001). These data provide robust baseline benchmarks for future hand hygiene intervention studies in these settings.Item The impact of automated hand hygiene monitoring with and without complementary improvement strategies on performance rates(Cambridge University Press, 2022-08) Arbogast, James W.; Moore, Lori D.; DiGiorgio, Megan; Robbins, Greg; Clark, Tracy L.; Thompson, Maria F.; Wagner, Pamela T.; Boyce, John M.; Parker, Albert E.Objective: To determine how engagement of the hospital and/or vendor with performance improvement strategies combined with an automated hand hygiene monitoring system (AHHMS) influence hand hygiene (HH) performance rates. Design: Prospective, before-and-after, controlled observational study. Setting: The study was conducted in 58 adult and pediatric inpatient units located in 10 hospitals. Methods: HH performance rates were estimated using an AHHMS. Rates were expressed as the number of soap and alcohol based hand rub portions dispensed divided by the number of room entries and exits. Each hospital self-assigned to one of the following intervention groups: AHHMS alone (control group), AHHMS plus clinician-based vendor support (vendor-only group), AHHMS plus hospital led unit-based initiatives (hospital-only group), or AHHMS plus clinician-based vendor support and hospital-led unit-based initiatives (vendor-plus-hospital group). Each hospital unit produced 1–2 months of baseline HH performance data immediately after AHHMS installation before implementing initiatives. Results: Hospital units in the vendor-plus-hospital group had a statistically significant increase of at least 46% in HH performance compared with units in the other 3 groups (P ≤ .006). Units in the hospital only group achieved a 1.3% increase in HH performance compared with units that had AHHMS alone (P = .950). Units with AHHMS plus other initiatives each had a larger change in HH performance rates over their baseline than those in the AHHMS-alone group (P < 0.001). Conclusions: AHHMS combined with clinician-based vendor support and hospital-led unit-based initiatives resulted in the greatest improvements in HH performance. These results illustrate the value of a collaborative partnership between the hospital and the AHHMS vendor.