The Effect of Automated Hand Hygiene Monitoring Systems and Other Complementary Behavior-Change Strategies on Performance

Background: Technology and interest for use of automated hand hygiene monitoring systems (AHHMS) as a tool to help improve healthcare personnel hand hygiene has been advancing for the last decade. Emerging evidence indicates that the use of AHHMS plus complementary strategies improves hand hygiene (HH) performance rates and outcomes (eg, healthcare-associated infections). The WHO HH guideline “Multimodal Strategy” teaches the importance of multiple components as necessary to build and sustain HH compliance. Few published data compare the impact of different complementary behavioral strategies in combination with AHHMS on results. Methods: We utilized data from 1 AHHMS that records alcohol-based hand rub and soap dispensing and room entries and exits to provide group HH performance rates. Data were collected from 58 units in 10 hospitals in North America from July 2014 through August 2019. Hospitals were stratified into 4 categories based on their approach to hospital-initiated unit-level interventions and AHHMS vendor support (Table 1). Baseline data were defined for each unit as the initial 1–2 months of execution, before complementary strategies were initiated. Statistical analysis was performed on the annual number of dispenses and opportunities with a mixed-effects Poisson regression with random effects for facility, unit and year and fixed effects for intervention type and unit type. Interactions were not included in the model based on interaction plots and significance tests. Poisson assumptions were verified with Pearson residual plots. Results: HH performance rates overall and compared to the baseline are shown in Table 2. More than 8 million opportunities were achieved in all 58 units combined. An intervention strategy with multiple complementary components (ie, clinical support provided by the AHHMS vendor plus hospital-initiated unit level interventions) yielded significantly better HH performance than all other categories (>20% increase, P < .00001). Somewhat surprisingly, vendor clinical support or hospital-initiated, unit-level interventions alone with the AHHMS yielded a slight decrease in HH performance relative to AHHMS only (P < .00001). Conclusions: AHHMS is a useful tool in understanding HH performance and identifying unit-based initiatives that need attention. Implementation of an AHHMS by itself or with limited complementary behavior-change strategies does not drive improvement. Support provided by the vendor and hospital-initiated, complementary strategies were not sufficient additions to the AHHMS individually, but in combination they resulted in the greatest improvements in HH performance. These findings illustrate the value of a partnership between the hospital and the AHHMS vendor. Funding: GOJO Industries, Inc., provided support for this study. Disclosures: James W. Arbogast, Lori D. Moore and Megan DiGiorgio report salary from GOJO Industries.