Relevance of intra-hospital patient movements for the spread of healthcareassociated infections within hospitals - A mathematical modeling study

Hannan Tahir*, Luis Eduardo Lopez-Cortes, Axel Kola, Dafna Yahav, Andre Karch, Hanjue Xia, Johannes Horn, Konrad Sakowski, Monika J. Piotrowska, Leonard Leibovici, Rafael T. Mikolajczyk, Mirjam E. Kretzschmar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

The aim of this study is to analyze patient movement patterns between hospital departments to derive the underlying intra-hospital movement network, and to assess if movement patterns differ between patients at high or low risk of colonization. For that purpose, we analyzed patient electronic medical record data from five hospitals to extract information on risk stratification and patient intra-hospital movements. Movement patterns were visualized as networks, and network centrality measures were calculated. Next, using an agent-based model where agents represent patients and intra-hospital patient movements were explicitly modeled, we simulated the spread of multidrug resistant enterobacteriacae (MDR-E) inside a hospital. Risk stratification of patients according to certain ICD-10 codes revealed that length of stay, patient age, and mean number of movements per admission were higher in the high-risk groups. Movement networks in all hospitals displayed a high variability among departments concerning their network centrality and connectedness with a few highly connected departments and many weakly connected peripheral departments. Simulating the spread of a pathogen in one hospital network showed positive correlation between department prevalence and network centrality measures. This study highlights the importance of intra-hospital patient movements and their possible impact on pathogen spread. Targeting interventions to departments of higher (weighted) degree may help to control the spread of MDR-E. Moreover, when the colonization status of patients coming from different departments is unknown, a ranking system based on department centralities may be used to design more effective interventions that mitigate pathogen spread.

Original languageEnglish
Article numbere1008600
JournalPLoS Computational Biology
Volume17
Issue number2
DOIs
StatePublished - 3 Feb 2021
Externally publishedYes

Funding

FundersFunder number
Netherlands ZonMw547001005
University Medical Centre Utrecht681055
Narodowe Centrum Nauki2016/ 22/Z/ST1/00690
Uniwersytet Warszawski01KI1704C

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