Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Healthcare Associated Infections I: Iatrogenic, Exogenic and Endogenic01:26

Healthcare Associated Infections I: Iatrogenic, Exogenic and Endogenic

5.3K
Healthcare-associated infections (HAIs) occur in a healthcare facility while a person receives care for another ailment. This category also includes work-related infections among healthcare staff.
HAIs significantly increase the cost of health care. Extended stays in healthcare institutions, increased disability, increased costs of medications, including specialized antibiotics, and prolonged recovery times add to the patient's expenses and the healthcare institution and funding bodies.
5.3K
Healthcare Associated Infections II: Preventive Measures01:22

Healthcare Associated Infections II: Preventive Measures

3.6K
Essential infection prevention measures are based on the knowledge of the infection chain, the modes of transmission in healthcare settings, and the use of the best practices in all healthcare settings. Compulsory public reporting of healthcare-associated infection rates is needed to allow individuals and the community to make informed choices regarding selecting a healthcare facility.
The best practices for preventing healthcare-associated infections include hand hygiene, patient risk...
3.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Implementing a participant-driven water management initiative to support Maryland hospitals.

Infection prevention in practice·2026
Same author

Alert fatigue measurement in clinical decision support: a systematic review.

Journal of the American Medical Informatics Association : JAMIA·2026
Same author

AI patient safety tools that augment human effort.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America·2026
Same author

Integrating Physical Therapy into Primary Care to Enhance Veteran Access to Healthcare: Findings from the Veterans Health Administration's PACT-PT Program.

Journal of general internal medicine·2026
Same author

Generative artificial intelligence for surgical site infection surveillance.

Infection control and hospital epidemiology·2026
Same author

Survival trends in patients with difficult-to-treat, antibiotic-resistant, Gram-negative infections in the era of next-generation antibiotics in the USA: a retrospective cohort study.

The Lancet. Infectious diseases·2026
Same journal

Wanted: A Relevant Correlate of Protection for Dengue Vaccines.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America·2026
Same journal

Safety and Immunogenicity of the Live-Attenuated Quadrivalent Dengue Vaccine V181 Compared With Butantan-DV Among Healthy Adults in Brazil: A Randomized, Double-Blind, Phase 2 Trial.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America·2026
Same journal

Low Post-Treatment Recurrence After a Shortened All-oral Regimen for Pulmonary Rifampicin- or Multidrug-Resistant Tuberculosis in Individuals without Prior Second-Line Drug Exposure in Kazakhstan.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America·2026
Same journal

Sepsis Diagnostic Excellence and its Association with Mortality in Adults with Potential Infection.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America·2026
Same journal

10-Year Trends in Attributable and Contributable Mortality of Culture-Positive Invasive Aspergillosis in Patients with Hematologic Malignancies: Have We Reached the "Ceiling Efficacy Effect" of Modern Antifungals?

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America·2026
Same journal

Virologic Outcomes After LA ART Initiation with and without Viremia in Two Large U.S. Clinic Cohorts.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America·2026
See all related articles

Related Experiment Video

Updated: Jan 11, 2026

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

2.4K

Using Generative Artificial Intelligence to Identify Central Line-associated Bloodstream Infections.

Daniel J Morgan1,2, Shatha AlShanqeeti1,3, K C Coffey1,2

  • 1Medical Care Center, VA Maryland Healthcare System, Veterans Health Administration, U.S. Department of Veterans Affairs, Baltimore, Maryland, USA.

Clinical Infectious Diseases : an Official Publication of the Infectious Diseases Society of America
|November 18, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) enhances central line-associated blood stream infection (CLABSI) detection, proving as accurate as manual review. AI-assisted review is faster, preferred by experts, and could improve healthcare-associated infection reporting.

Keywords:
Central line–associated blood stream infection (CLABSI)Generative AISurveillance

More Related Videos

Author Spotlight: Accelerating Diagnostic Accuracy with Direct Identification of Gram-Negatives from Blood Culture Bottles
09:07

Author Spotlight: Accelerating Diagnostic Accuracy with Direct Identification of Gram-Negatives from Blood Culture Bottles

Published on: May 24, 2024

1.4K
Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence
09:11

Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence

Published on: January 27, 2023

2.7K

Related Experiment Videos

Last Updated: Jan 11, 2026

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

2.4K
Author Spotlight: Accelerating Diagnostic Accuracy with Direct Identification of Gram-Negatives from Blood Culture Bottles
09:07

Author Spotlight: Accelerating Diagnostic Accuracy with Direct Identification of Gram-Negatives from Blood Culture Bottles

Published on: May 24, 2024

1.4K
Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence
09:11

Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence

Published on: January 27, 2023

2.7K

Area of Science:

  • Healthcare quality improvement
  • Infectious disease surveillance
  • Artificial intelligence in medicine

Background:

  • Central line-associated blood stream infection (CLABSI) surveillance is a mandated process in US hospitals.
  • Current CLABSI surveillance relies on manual chart review, which is time-consuming.
  • Generative artificial intelligence (AI) presents a potential solution for automating and improving CLABSI identification.

Purpose of the Study:

  • To evaluate the accuracy and efficiency of AI-assisted CLABSI surveillance compared to traditional methods.
  • To assess healthcare professionals' preferences regarding AI-driven surveillance tools.
  • To determine the potential of AI to enhance the accuracy and reduce variability in healthcare-associated infection reporting.

Main Methods:

  • A retrospective cohort study was conducted across 11 hospitals.
  • Standardized prompts, clinical data, and CDC definitions were used for CLABSI surveillance.
  • Three review methods were compared: AI-assist, AI-alone, and repeat expert review, with adjudication by a physician panel.

Main Results:

  • AI-assist review demonstrated 93.2% accuracy, surpassing AI-alone (90.0%) and repeat expert review (88.2%).
  • AI-assist review was significantly faster (14 minutes median) and perceived as lower effort (52% vs. 21%) than repeat expert review.
  • AI-assist review showed less inter-site variability compared to repeat expert review.

Conclusions:

  • AI-based methods for CLABSI detection are at least as accurate as traditional manual review.
  • AI-assisted review is preferred by healthcare experts due to speed, reduced effort, and objectivity.
  • Implementing AI in CLABSI surveillance can potentially improve the efficiency and reliability of healthcare-associated infection reporting.