ChatGPT-4 for Surgical Site Infection Detection From Electronic Health Records After Colorectal Surgery. (Infect-IA-3)
Evaluation of ChatGPT-4 for the Detection of Surgical Site Infections From Electronic Health Records After Colorectal Surgery: A Diagnostic Accuracy Study.
Epidemiological surveillance is one of the eight core components of the World Health Organization Infection Prevention and Control Programmes. These include surveillance programmes for surgical site infection (SSI).
At present, for SSI surveillance, infection control teams perform a manual time-consuming work, which could make a transition to automated surveillance leveraging the new information technology.
This study aimed to evaluate the ability of ChatGPT-4o to detect surgical site infection at the three anatomical levels.
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Healthcare-associated infections (HAIs) have a negative impact on patient health, represent a significant healthcare and economic burden on healthcare systems and are considered the most preventable cause of serious adverse events in hospitalised patients.
Epidemiological surveillance is one of the eight core components of the World Health Organization (WHO) Infection Prevention and Control Programmes. These include surveillance programmes for surgical site infection (SSI), which have proven to be effective in all types of surgery and in a variety of settings.
For a programme to be effective, surveillance for HCAIs must be active, prospective and continuous, comprising a surveillance period up to 30-90 days post-intervention, to cover the high rate of SSIs detected after discharge.
At present, infection control teams perform a manual, prospective, time-consuming and almost artisanal work, which should make a transition to automated or semi-automated surveillance that leverages the possibilities offered by today's information technology.
The evolution of surveillance systems should benefit from this new possibilities offered by artificial intelligence, allowing automated detection of suspected SSI adverse events from clinical course text, microbiology reports or coding of diagnoses, procedures, complications and readmissions.
This study aims to evaluate the ability of ChatGPT to detect surgical site infections (SSI) at the three anatomical levels described by the CDC.
The study will retrospectively compare the results of the AI chatbot in diagnosing SSI, trained using the US CDC definition criteria, with a large cohort of elective colorectal surgery patients already evaluated through a nationwide nosocomial infection surveillance system, which will be the comparative gold standard.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Contact
- Name: Josep Badia, MD, PhD
- Phone Number: 670702099
- Email: jmbadiaperez@gmail.com
Study Locations
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Barcelona
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Granollers, Barcelona, Spain, 08402
- Recruiting
- Hospital General de Granollers
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Contact:
- Josep M Badia
- Phone Number: 670702099
- Email: jmbadiaperez@gmail.com
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-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Elective colorectal resection
Exclusion Criteria:
- Emergency surgery
- Infection present at operation
- Previous intestinal stoma
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
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Patients assessed for SSI using the standard manual surveillance method
Patients undergoing colorectal surgery enrolled in the nationwide SSI surveillance programme and assessed for SSI using the standard manual surveillance method.
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Diagnosis of SSI by manual system in colorectal surgery procedures enrolled in the SSI surveillance programme.
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Patients assessed for SSI by Open IA's ChatGPT 4 chatbot
Patients undergoing colorectal surgery enrolled in the nationwide SSI surveillance programme and assessed for SSI using the Open IA's ChatGPT 4 chatbot.
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Diagnosis of SSI by manual system in colorectal surgery procedures enrolled in the SSI surveillance programme.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Rate of surgical site infection
Time Frame: 30 days
|
Rate of Surgical site infection according to the definitions of the CDC-NHSN (Centers for Disease Control and Prevention-National Healthcare Safety Network)
|
30 days
|
Collaborators and Investigators
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Estimated)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- Infect-IA-3
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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