A Data Mining System for Infection Control Surveillance

Nosocomial infections and antimicrobial resistance are problems of enormous magnitude that impact the morbidity and mortality of hospitalized patients as well as their cost of care. The Data Mining Surveillance System (DMSS) uses novel data mining techniques to discover unsuspected, useful patterns of nosocomial infections and antimicrobial resistance from the analysis of hospital laboratory data. This report details a mature version of DMSS as well as an experiment in which DMSS was used to analyze all inpatient culture data, collected over 15 months at the University of Alabama at Birmingham Hospital.

[1]  R M Gardner,et al.  Computer surveillance of hospital-acquired infections and antibiotic use. , 1986, JAMA.

[2]  R N Jones,et al.  The current and future impact of antimicrobial resistance among nosocomial bacterial pathogens. , 1992, Diagnostic microbiology and infectious disease.

[3]  F. Koontz,et al.  A review of traditional resistance surveillance methodologies and infection control. , 1992, Diagnostic microbiology and infectious disease.

[4]  R N Jones,et al.  Antibiotic resistance. Epidemiology and therapeutics. , 1992, Diagnostic microbiology and infectious disease.

[5]  J A Sellick,et al.  The use of statistical process control charts in hospital epidemiology. , 1993, Infection control and hospital epidemiology.

[6]  R A Weinstein,et al.  Strategies to Prevent and Control the Emergence and Spread of Antimicrobial-Resistant Microorganisms in Hospitals. A challenge to hospital leadership. , 1996, JAMA.

[7]  K. Waites,et al.  Genotypic investigation of multidrug-resistant Acinetobacter baumannii infections in a medical intensive care unit. , 1997, The Journal of hospital infection.

[8]  D. Gerding,et al.  Society for Healthcare Epidemiology of America and Infectious Diseases Society of America Joint Committee on the Prevention of Antimicrobial Resistance: guidelines for the prevention of antimicrobial resistance in hospitals. , 1997, Infection control and hospital epidemiology.

[9]  Warren T. Jones,et al.  Research Paper: Association Rules and Data Mining in Hospital Infection Control and Public Health Surveillance , 1998, J. Am. Medical Informatics Assoc..

[10]  T. Clemmer,et al.  A computer-assisted management program for antibiotics and other antiinfective agents. , 1998, The New England journal of medicine.