Understanding provider-level properties that influence the transmission of healthcare associated infections using network analysis

Hyojung Kang, Marika E. Waselewski, Jennifer M. Lobo

Research output: Contribution to journalArticle

Abstract

The goal of this study is to determine which provider-level properties (e.g., provider types, patient contact factors) of healthcare workers (HCW) have the greatest impact on the transmission of healthcare associated infections (HAIs). This study focused on Carbapenem-resistant Enterobacteriaceae (CRE) acquisition for patients who stayed in a long-term acute care hospital (LTACH) in central Virginia during July and August 2014. We used both patient data (e.g., bed movement, screening results for CRE) and provider activity data documented through the electronic medical record. We created a network of patients for each HCW and performed Poisson regression analysis including the network measures. A total of 204 providers saw at least one of the nine positive patients who stayed in the LTACH over the study period. From the Poisson regression, provider types, total number of patients each provider saw, LTACH workdays, average number of patients per day during LTACH workdays, and the provider's network were associated with the frequency of case contact. Our study demonstrated that in addition to patient data, provider activity logs that show provider-level properties can be used to assess the role of healthcare workers in transmitting HAIs and highlight risk mitigation opportunities.

Original languageEnglish (US)
Article number100223
JournalOperations Research for Health Care
Volume23
DOIs
StatePublished - Dec 2019

Keywords

  • Electronic medical records
  • Hospital associated infections
  • Network model
  • Poisson regression
  • Provider activity logs

ASJC Scopus subject areas

  • Surgery
  • Oral Surgery
  • Otorhinolaryngology

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