21 Million Opportunities: a 19 Facility Investigation of Factors Affecting Hand-Hygiene Compliance via Linear Predictive Models
| Autor: | Michael T. Lash, Jason Slater, Alberto M. Segre, Philip M. Polgreen |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
business.industry
media_common.quotation_subject Health Informatics Predictive analytics Affect (psychology) Health informatics Computer Science Applications Compliance (psychology) Artificial Intelligence Hygiene Environmental health Linear regression business Psychology Feature ranking Research Article Information Systems media_common |
| Zdroj: | J Healthc Inform Res |
| ISSN: | 2509-498X 2509-4971 |
| DOI: | 10.1007/s41666-019-00048-1 |
| Popis: | 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. We examine the use of features such as temperature, relative humidity, influenza severity, day/night shift, federal holidays, and the presence of new medical residents in predicting daily hand-hygiene compliance; the investigation is undertaken using both a “global” model to glean general trends and facility-specific models to elicit facility-specific insights. 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 exist among facilities. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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