NIHR Biomedical Research Centre: Oxford

Enabling translational research through partnership

NIHR 20th Anniversary NIHR website
NIHR Biomedical Research Centre: Oxford
  • Home
  • About
    • About us
    • Impact
    • Our next BRC
    • Steering Committee
    • Promoting equality, diversity and inclusion in research
    • Current Vacancies
    • Stay in Touch
    • Contact Us
  • Research
    • Research Overview
      • NIHR Clinical Research Facility
      • Ethics in the NIHR BRC: Oxford
      • Health Economics
      • Medical Statistics
    • Cancer
    • Cardiovascular Medicine
    • Digital Health from Hospital to Home
    • Gene and Cell Therapy
    • Genomic Medicine
    • Imaging
    • Inflammation across Tissues
    • Life-saving Vaccines
    • Metabolic Experimental Medicine
    • Modernising Medical Microbiology and Big Infection Diagnostics
      • Theme overview
      • Infections in Oxfordshire Database (IORD)
    • Musculoskeletal
    • Preventive Neurology
    • Respiratory Medicine
    • Surgical Innovation, Technology and Evaluation
    • Translational Data Science
  • Patient & Public Involvement
    • For patients and the public
    • For researchers
    • More information
  • Training
  • Industry & Partnerships
  • News
  • Events
  • Videos

Research Theme

IORD Project

Can we identify surgical site infections using routine electronic health record data?

COMPLETED
IORD category: Electronic Health Records, Specific Infections
Chief Investigator: Prof Sarah Walker
Sponsor: OUH
Research location: Oxford University
Approval date: 25 Feb 2015

Millions of operations are carried out in the NHS every year. Infection is a rare but important complication that can happen after surgery. Specific operations are routinely monitored every year in every NHS hospital to see how often these post-surgery infections occur. This is very time-consuming as it is done in person by an infection control nurse for 3 months every year in every hospital, and continuously in cardiac surgery. Even then, the nurses are only able to follow-up patients whilst they are in hospital, and cannot find out if patients get infections after they have been discharged. Every time a person comes to hospital or has an operation, a large amount of routine electronic data is recorded, including about the operation (what type it was, how long it went on for), what blood tests were done and what was found, how long people stayed in different wards for etc. In this project we want to try to use this data to see if we can accurately and reliably predict who developed post-surgery infections, using the data collected by hand by the nurse as the “gold standard”. If we can do this, we could monitor these infections throughout the year.

Modernising Medical Microbiology icon

Modernising Medical Microbiology and Big Infection Diagnostics

  • Theme overview
  • Sub-theme 1: Novel rapid, high-throughput diagnostic workflows for infection
  • Sub-theme 2: Big data-led infection diagnosis and management strategies
  • Contacts
  • Videos
  • News

Infections in Oxfordshire Research Database (IORD)

  • IORD Overview
    • What data is in IORD?
    • Different kinds of data in IORD
    • Who can use the data?
    • How do they get the data?
    • What do they do with the data?
    • What kind of questions has IORD answered? Why is this important?
    • What was it like before IORD?
    • Opting out
  • IORD Application Trajectory
  • IORD Projects
  • IORD Publications
  • IORD Privacy Notice
  • IORD Glossary
  • IORD FAQs
  • IORD Infographics
You are here: Home > IORD > Can we identify surgical site infections using routine electronic health record data?

Subscribe to the BRC Oxford Newsletter

Keep informed about the work of the BRC Oxford by subscribing to our Mailchimp e-newsletter. It is produced several times a year and delivers news and information about upcoming events straight to your inbox.

Subscribe Now

Feedback

We’d love to hear your feedback. Please contact us at obrcenquiries@ouh.nhs.uk

BRC Oxford on Social Media

  • Bluesky
  • Facebook
  • LinkedIn
  • YouTube
  • Data Control and Privacy
  • Accessibility
  • Our Partners
  • Disclaimer
  • Contact

Copyright © 2026 NIHR Biomedical Research Centre: Oxford