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Item Drastic hourly changes in hand hygiene workload and performance rates: A multicenter time series analysis(Elsevier BV, 2024-09) Moore, Lori D.; Arbogast, James W.; Robbins, Greg; DiGiorgio, Megan; Parker, Albert E.Background. High hand hygiene (HH) workload is a commonly cited barrier to optimal HH performance. The objective of this study was to assess trends of HH workload as defined by HH opportunities (HHO) and performance rates over different timescales using automated HH monitoring system data. Methods. This multiyear retrospective observational study was conducted in 58 inpatient units located in 10 North American hospitals. HHO and HH rates were analyzed by time series mixed effects general additive model. Results. Median HH rates peaked at 50.0 between 6 and 7 AM with a trough of 38.2 at 5 PM. HHO over hours in a day were the highest at 184 per hospital unit per hour at 10 AM with a trough of 49.0 between 2 and 3 AM. Median rates for day and night shifts were 40.8 and 45.5, respectively (P = .078). Weekend day shift had the lowest median rate (39.4) compared with any other 12-hour shift (P < .1018). The median rates and HHO varied little across days in a week and months. Conclusions. HH workload and performance rates were negatively correlated and changed drastically over hours in a day. Hospitals should consider HH workload in the development and timely delivery of improvement interventions.Item Drastic hourly changes in hand hygiene workload and performance rates: a multicenter time series analysis(Elsevier BV, 2024-09) Moore, Lori; Arbogast, James W.; Robbins, Greg; DiGiorgio, Megan; Parker, Albert E.Background. High hand hygiene (HH) workload is a commonly cited barrier to optimal HH performance. The objective of this study was to assess trends of HH workload as defined by HH opportunities (HHO) and performance rates over different timescales using automated HH monitoring system data. Methods. This multiyear retrospective observational study was conducted in 58 inpatient units located in 10 North American hospitals. HHO and HH rates were analyzed by time series mixed effects general additive model. Results. Median HH rates peaked at 50.0 between 6 and 7 AM with a trough of 38.2 at 5 PM. HHO over hours in a day were the highest at 184 per hospital unit per hour at 10 AM with a trough of 49.0 between 2 and 3 AM. Median rates for day and night shifts were 40.8 and 45.5, respectively (P = .078). Weekend day shift had the lowest median rate (39.4) compared with any other 12-hour shift (P < .1018). The median rates and HHO varied little across days in a week and months. Conclusions. HH workload and performance rates were negatively correlated and changed drastically over hours in a day. Hospitals should consider HH workload in the development and timely delivery of improvement interventions.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.