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To measure the impact of an automated hand hygiene monitoring system (AHHMS) and an intervention program of complementary strategies on hand hygiene (HH) performance in both acute-care and long-term care (LTC) units.
Prospective, nonrandomized, before-and-after intervention study.
Single Veterans Affairs Medical Center (VAMC), with 2 acute-care units and 6 LTC units.
An AHHMS that provides group HH performance rates was implemented on 8 units at a VAMC from March 2021 through April 2022. After a 4-week baseline period and 2.5-week washout period, the 52-week intervention period included multiple evidence-based components designed to improve HH compliance. Unit HH performance rates were expressed as the number of dispenses (events) divided by the number of patient room entries and exits (opportunities) × 100. Statistical analysis was performed with a Poisson general additive mixed model.
During the 4-week baseline period, the median HH performance rate was 18.6 (95% CI, 16.5–21.0) for all 8 units. During the intervention period, the median HH rate increased to 21.6 (95% CI, 19.1–24.4; P < .0001), and during the last 4 weeks of the intervention period (exactly 1 year after baseline), the 8 units exhibited a median HH rate of 25.1 (95% CI, 22.2–28.4; P < .0001). The median HH rate increased from 17.5 to 20.0 (P < .0001) in LTC units and from 22.9 to 27.2 (P < .0001) in acute-care units.
The intervention was associated with increased HH performance rates for all units. The performance of acute-care units was consistently higher than LTC units, which have more visitors and more mobile veterans.
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.
Prospective, before-and-after, controlled observational study.
The study was conducted in 58 adult and pediatric inpatient units located in 10 hospitals.
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.
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).
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.
Determine the impact of an automated hand hygiene monitoring system (AHHMS) plus complementary strategies on hand hygiene performance rates and healthcare-associated infections (HAIs).
Retrospective, nonrandomized, observational, quasi-experimental study.
Single, 93-bed nonprofit hospital.
Hand hygiene compliance rates were estimated using direct observations. An AHHMS, installed on 4 nursing units in a sequential manner, determined hand hygiene performance rates, expressed as the number of hand hygiene events performed upon entering and exiting patient rooms divided by the number of room entries and exits. Additional strategies implemented to improve hand hygiene included goal setting, hospital leadership support, feeding AHHMS data back to healthcare personnel, and use of Toyota Kata performance improvement methods. HAIs were defined using National Healthcare Safety Network criteria.
Hand hygiene compliance rates generated by direct observation were substantially higher than performance rates generated by the AHHMS. Installation of the AHHMS without supplementary activities did not yield sustained improvement in hand hygiene performance rates. Implementing several supplementary strategies resulted in a statistically significant 85% increase in hand hygiene performance rates (P < .0001). The incidence density of non–Clostridioies difficile HAIs decreased by 56% (P = .0841), while C. difficile infections increased by 60% (P = .0533) driven by 2 of the 4 study units.
Implementation of an AHHMS, when combined with several supplementary strategies as part of a multimodal program, resulted in significantly improved hand hygiene performance rates. Reductions in non–C. difficile HAIs occurred but were not statistically significant.
Clouds of dispersed explosive or combustible solid particles are detonable and such systems may exhibit self-sustained detonation [1–8]. However, the method by which individual particles in the explosive cloud interact to sustain detonation is not well understood. The similar case of liquid fuel/air explosives was investigated in detail during the 1960's and 1970's. For these systems, it was established that incident shock waves serve to shatter large liquid droplets into a mist of micro-droplets. These microdroplets are almost instantaneously accelerated to the convective flow velocity behind the shock wave. The energy released upon ignition of the micromist supports the shock wave and selfsustained detonation results [9–11].
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