A Large-Scale Exploration of Factors Affecting Hand Hygiene Compliance Using Linear Predictive Models
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.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
21 Million Opportunities: A 19 Facility Investigation of Factors Affecting Hand Hygiene Compliance via Linear Predictive Models
This large-scale study, consisting of 21.3 million hand hygiene opportunities from 19 distinct facilities in 10 different states, uses linear predictive models to expose factors that may affect hand hygiene compliance. W…
M6-T: Exploring Sparse Expert Models and Beyond
Mixture-of-Experts (MoE) models can achieve promising results with outrageous large amount of parameters but constant computation cost, and thus it has become a trend in model scaling. Still it is a mystery how MoE layer…
Mixture-of-ExpertsPlaying the Game of 2048On-Road Object Importance Estimation: A New Dataset and A Model with Multi-Fold Top-Down Guidance
This paper addresses the problem of on-road object importance estimation, which utilizes video sequences captured from the driver's perspective as the input. Although this problem is significant for safer and smarter dri…
ObjectWetin dey with these comments? Modeling Sociolinguistic Factors Affecting Code-switching Behavior in Nigerian Online Discussions
Multilingual individuals code switch between languages as a part of a complex communication process. However, most computational studies have examined only one or a handful of contextual factors predictive of switching. …
ArticlesPrediction of Clinical Risk Factors of Diabetes Using Multiple Machine Learning Techniques Resolving Class Imbalance
Prediction of Clinical Risk Factors of Diabetes Using Multiple Machine Learning TechBeing the most common and rapidly growing disease, Diabetes affecting a huge number of people from all span of ages each year that reduc…
BIG-bench Machine LearningMedical Diagnosis