ArticleJournal of the American Medical Informatics Association : JAMIA2013
A social network of hospital acquired infection built from electronic medical record data.
Article in Journal of the American Medical Informatics Association : JAMIA, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.
- Applications of network analysis to routinely collected health care data: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2018Pooled it
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- Healthcare personnel interactive pathogen exposure response system.Infection control and hospital epidemiology · 2023Article
- GRANDPA: GeneRAtive network sampling using degree and property augmentation applied to the analysis of partially confidential healthcare networks.Applied network science · 2023Article
- Investigating healthcare worker mobility and patient contacts within a UK hospital during the COVID-19 pandemic.Communications medicine · 2022Article
- A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.Frontiers in public health · 2022Article
- Use of clinical data to augment healthcare worker contact tracing during the COVID-19 pandemic.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Evaluation of nosocomial infections through contact patterns in a small animal hospital using social network analysis and genotyping techniques.Scientific reports · 2021Article
- A Social Network Analysis Approach for Contact Tracing in the Hospital Setting.Delaware journal of public health · 2020Article
- The Role of Healthcare Worker-Mediated Contact Networks in the Transmission of Vancomycin-ResistantOpen forum infectious diseases · 2020Article
- Contact among healthcare workers in the hospital setting: developing the evidence base for innovative approaches to infection control.BMC infectious diseases · 2018Article
- Strong social relationships are associated with decreased longevity in a facultatively social mammal.Proceedings. Biological sciences · 2018Article
- How next-generation sequencing and multiscale data analysis will transform infectious disease management.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2015Article
- Clinical differences between H3N2 and H1N1 influenza 2012 and lower respiratory tract infection found using a statistical classification approach.Therapeutics and clinical risk management · 2014Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
objectiveSocial networks have been used in the study of outbreaks of infectious diseases, including in small group settings such as individual hospitals. Collecting the data needed to create such networks, however, can be time consuming, costly, and error prone. We sought to create a social network of hospital inpatients using electronic medical record (EMR) data already collected for other purposes, for use in simulating outbreaks of nosocomial infections. MATERIALS AND
methodsWe used the EMR data warehouse of a tertiary academic hospital to model contact among inpatients. Patient-to-patient contact due to shared rooms was inferred from admission-discharge-transfer data, and contact with healthcare workers was inferred from clinical documents. Contacts were used to generate a social network, which was then used to conduct probabilistic simulations of nosocomial outbreaks of methicillin-resistant Staphylococcus aureus and influenza.
resultsSimulations of infection transmission across the network reflected the staffing and patient flow practices of the hospital. Simulations modeling patient isolation, increased hand hygiene, and staff vaccination showed a decrease in the spread of infection. DISCUSSION: We developed a method of generating a social network of hospital inpatients from EMR data. This method allows the derivation of networks that reflect the local hospital environment, obviate the need for simulated or manually collected data, and can be updated in near real time.
conclusionsInpatient social networks represent a novel secondary use of EMR data, and can be used to simulate nosocomial infections. Future work should focus on prospective validation of the simulations, and adapting such networks to other tasks.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.