title: Healthcare worker contact networks and the prevention of hospital-acquired infections.
abstract: We present a comprehensive approach to using electronic medical records (EMR) for constructing contact networks of healthcare workers in a hospital. This approach is applied at the University of Iowa Hospitals and Clinics (UIHC)--a 3.2 million square foot facility with 700 beds and about 8,000 healthcare workers--by obtaining 19.8 million EMR data points, spread over more than 21 months. We use these data to construct 9,000 different healthcare worker contact networks, which serve as proxies for patterns of actual healthcare worker contacts. Unlike earlier approaches, our methods are based on large-scale data and do not make any a priori assumptions about edges (contacts) between healthcare workers, degree distributions of healthcare workers, their assignment to wards, etc. Preliminary validation using data gathered from a 10-day long deployment of a wireless sensor network in the Medical Intensive Care Unit suggests that EMR logins can serve as realistic proxies for hospital-wide healthcare worker movement and contact patterns. Despite spatial and job-related constraints on healthcare worker movement and interactions, analysis reveals a strong structural similarity between the healthcare worker contact networks we generate and social networks that arise in other (e.g., online) settings. Furthermore, our analysis shows that disease can spread much more rapidly within the constructed contact networks as compared to random networks of similar size and density. Using the generated contact networks, we evaluate several alternate vaccination policies and conclude that a simple policy that vaccinates the most mobile healthcare workers first, is robust and quite effective relative to a random vaccination policy.
authors.affiliation: Department of Computer Science, The University of Iowa, Iowa City, Iowa, United States of America.
authors.forename: Donald E
authors.initials: DE
authors.lastname: Curtis
authors.affiliation: Department of Computer Science, The University of Iowa, Iowa City, Iowa, United States of America.
authors.forename: Christopher S
authors.initials: CS
authors.lastname: Hlady
authors.affiliation: Department of Computer Science, The University of Iowa, Iowa City, Iowa, United States of America.
authors.forename: Gaurav
authors.initials: G
authors.lastname: Kanade
authors.affiliation: Department of Computer Science, The University of Iowa, Iowa City, Iowa, United States of America.
authors.forename: Sriram V
authors.initials: SV
authors.lastname: Pemmaraju
authors.affiliation: Department of Internal Medicine, The University of Iowa, Iowa City, Iowa, United States of America.
authors.forename: Philip M
authors.initials: PM
authors.lastname: Polgreen
authors.affiliation: Department of Computer Science, The University of Iowa, Iowa City, Iowa, United States of America.
authors.forename: Alberto M
authors.initials: AM
authors.lastname: Segre
mesh_terms: D003428:Cross Infection / Q000517:prevention & control* / Q000635:transmission; D057286:Electronic Health Records; D006282:Health Personnel; D006761:Hospitals; D006801:Humans; D060756:Social Networking; D014611:Vaccination