21 Million Opportunities: a 19 Facility Investigation of Factors Affecting Hand-Hygiene Compliance via Linear Predictive Models

Michael T Lash; Jason Slater; Philip M Polgreen; Alberto M Segre

doi:10.1007/s41666-019-00048-1

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21 Million Opportunities: a 19 Facility Investigation of Factors Affecting Hand-Hygiene Compliance via Linear Predictive Models

Journal article

Open access

21 Million Opportunities: a 19 Facility Investigation of Factors Affecting Hand-Hygiene Compliance via Linear Predictive Models

Michael T Lash, Jason Slater, Philip M Polgreen and Alberto M Segre

Journal of healthcare informatics research, Vol.3(4), pp.393-413

04/29/2019

DOI: 10.1007/s41666-019-00048-1

PMCID: PMC8982796

PMID: 35415431

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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982796View

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Abstract

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.

Biomedical Engineering and Bioengineering

Computational Biology/Bioinformatics

Computational Intelligence

Computer Science

Data Mining and Knowledge Discovery

Health Informatics

Research Article

Details

Title: Subtitle: 21 Million Opportunities: a 19 Facility Investigation of Factors Affecting Hand-Hygiene Compliance via Linear Predictive Models
Creators: Michael T Lash - University of Iowa
Jason Slater - Gojo
Philip M Polgreen - University of Iowa
Alberto M Segre - University of Iowa
Resource Type: Journal article
Publication Details: Journal of healthcare informatics research, Vol.3(4), pp.393-413
DOI: 10.1007/s41666-019-00048-1
PMID: 35415431
PMCID: PMC8982796
NLM abbreviation: J Healthc Inform Res
ISSN: 2509-4971
eISSN: 2509-498X
Publisher: Springer International Publishing
Grant note: GOJO Industries, Inc.
Language: English
Date published: 04/29/2019
Academic Unit: Infectious Diseases; Epidemiology; Nursing; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Computer Science; Business Analytics; Internal Medicine
Record Identifier: 9984259503102771

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