Network analysis of intra-hospital transfers and hospital onset clostridium difficile infection

Health Info Libr J. 2020 Mar;37(1):26-34. doi: 10.1111/hir.12274. Epub 2019 Oct 19.

Abstract

Objectives: To explore how social network analysis (SNA) can be used to analyse intra-hospital patient networks of individuals with a hospital acquired infection (HAI) for further analysis in a geographical information systems (GIS) environment.

Methods: A case and control study design was used to select 2008 patients. We retrieved locational data for the patients, which was then translated into a network with the SNA software and then GIS software. Overall metrics were calculated for the SNA based on three datasets and further analysed with a GIS.

Results: The SNA analysis compared cases to control indicating significant differences in the overall structure of the networks. A GIS visual representation of these metrics was developed, showing spatial variation across the example hospital floor.

Discussion: This study confirmed the importance that intra-hospital patient networks play in the transmission of HAIs, highlighting opportunities for interventions utilising these data. Due to spatial variation differences, further research is necessary to confirm this is not a localised phenomenon, but instead a common situation occurring within many hospitals.

Conclusion: Utilising SNA and GIS analysis in conjunction with one another provided a data-rich environment in which the risk inherent in intra-hospital transfer networks was quantified, visualised and interpreted for potential interventions.

Keywords: communicable diseases; information science; information systems; public health.

MeSH terms

  • Case-Control Studies
  • Clostridioides difficile / drug effects
  • Clostridioides difficile / pathogenicity*
  • Clostridium Infections / epidemiology
  • Clostridium Infections / prevention & control*
  • Cross Infection / epidemiology
  • Cross Infection / prevention & control
  • Geographic Mapping
  • Humans
  • Iatrogenic Disease / epidemiology
  • Iatrogenic Disease / prevention & control*
  • Patient Transfer / standards*
  • Patient Transfer / statistics & numerical data
  • Social Networking