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 Experiment Videos

A data mining system for infection control surveillance.

S E Brossette1, A P Sprague, W T Jones

  • 1Department of Pathology, University of Alabama at Birmingham, USA.

Methods of Information in Medicine
|February 24, 2001
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Patient-level analysis of incident vancomycin-resistant enterococci colonization and antibiotic days of therapy.

Epidemiology and infection·2016
Same author

Growth rates are related to production efficiencies in juveniles of the sea urchin <i>Lytechinus variegatus.</i>

Journal of the Marine Biological Association of the United Kingdom. Marine Biological Association of the United Kingdom·2014
Same author

A genetic polymorphism for tannin production in Lotus corniculatus and its relationship to cyanide polymorphism.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2013
Same author

The origin of Lotus corniculatus.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2013
Same author

Characterization of metals released from coal fly ash during dredging at the Kingston ash recovery project.

Chemosphere·2013
Same author

Comparative genotyping of Streptococcus mutans by repetitive extragenic palindromic polymerase chain reaction and multilocus sequence typing.

Molecular oral microbiology·2012
Same journal

Design and methodological development of a digital clinical safety training programme informed by a national framework: a New Zealand case study.

Methods of information in medicine·2026
Same journal

Panic Prediction from Digital Phenotyping: Subject-Level Cross-Validation Reveals Limited Between-Person Generalization.

Methods of information in medicine·2026
Same journal

Agent-Based Modeling Approach for Population Dynamics of the Biological Vector Aedes Aegypti.

Methods of information in medicine·2026
Same journal

A Statistical Framework for Person-centered Analysis of Digital Service Use in Public Health and Social Care.

Methods of information in medicine·2026
Same journal

Assessing the Quality of Electronic Discharge Summaries: A Cross-Sectional Study Using the Validated Spanish Version of the PDQI-9.

Methods of information in medicine·2026
Same journal

A Knowledge Graph-Driven Hypergeometric Efficacy Prediction Model for Classical Traditional Chinese Herbal Formulas.

Methods of information in medicine·2026
See all related articles

The Data Mining Surveillance System (DMSS) identifies hospital-acquired infections and antimicrobial resistance using novel data mining. This system analyzes laboratory data to uncover hidden patterns, improving patient care and reducing costs.

Area of Science:

  • Clinical Informatics
  • Infectious Diseases
  • Health Services Research

Background:

  • Nosocomial infections and antimicrobial resistance pose significant threats to hospitalized patients, increasing morbidity, mortality, and healthcare costs.
  • Effective surveillance systems are crucial for early detection and management of these healthcare-associated challenges.

Purpose of the Study:

  • To present a mature version of the Data Mining Surveillance System (DMSS).
  • To evaluate DMSS's capability in discovering previously unknown patterns of nosocomial infections and antimicrobial resistance.
  • To analyze hospital laboratory data for improved infection control.

Main Methods:

  • Utilized novel data mining techniques within the DMSS framework.
  • Analyzed comprehensive inpatient culture data collected over 15 months.

Related Experiment Videos

  • Applied DMSS to identify unsuspected patterns in infection and resistance data.

    • Main Results:

    • The DMSS successfully identified useful, previously undiscovered patterns in nosocomial infections and antimicrobial resistance.
    • The system demonstrated efficacy in analyzing large-scale hospital laboratory data.
    • The findings provide insights into infection trends and resistance mechanisms.

    Conclusions:

    • The Data Mining Surveillance System (DMSS) is an effective tool for uncovering critical patterns in hospital-acquired infections and antimicrobial resistance.
    • DMSS analysis of laboratory data can enhance surveillance and inform infection control strategies.
    • This approach holds potential for improving patient outcomes and optimizing healthcare resource allocation.