A Large-Scale Exploration of Factors Affecting Hand Hygiene Compliance Using Linear Predictive Models
This research addresses hand hygiene compliance in healthcare settings, providing insights for infection control, but it is incremental as it applies standard linear models to a large dataset.
The study analyzed 24.5 million hand hygiene opportunities across 19 facilities to identify factors affecting compliance, finding that colder temperatures and federal holidays negatively impact rates and that facility-specific cultures influence behavior.
This large-scale study, consisting of 24.5 million hand hygiene opportunities spanning 19 distinct facilities in 10 different states, uses linear predictive models to expose factors that may affect hand hygiene compliance. We examine the use of features such as temperature, relative humidity, influenza severity, day/night shift, federal holidays and the presence of new residents in predicting daily hand hygiene compliance. The results suggest that colder temperatures and federal holidays have an adverse effect on hand hygiene compliance rates, and that individual cultures and attitudes regarding hand hygiene seem to exist among facilities.