title: The application of information technology to regional, national, and global surveillance of antimicrobial resistance.
abstract: Establishing local, national, and global surveillance networks for monitoring the dissemination of antimicrobial resistance and detecting the emergence of new resistance mechanisms has been recommended by the American Society for Microbiology Task Force on Antibiotic Resistance and other national organizations. While the need to develop and deploy surveillance strategies cannot be argued, the design and implementation of effective regional, national, and global surveillance networks is a daunting task with geographic, participatory, logistic, and funding challenges. Using information technology to capture, combine, collate, and analyze daily clinical microbiology laboratory data would seem to be a far more robust and logical approach to surveillance than traditional centralized studies that generally focus on only a few bacterial species or on isolates from a single body site. Information technology allows long-term, continuous tracking of antimicrobial resistance trends among large numbers of isolates over a broad range of species, and across entire regions or countries. The rationale for wanting to use networks of clinical laboratories for surveillance is obvious: susceptibility data are generated every day by thousands of laboratories located around the world, and most of these laboratories perform antimicrobial susceptibility testing on the bacterial species that pose the greatest public health problems. By virtue of information technology, large volumes of data can readily be managed and stored to allow timely and thorough analysis on institutional, regional, national, and global levels.
authors.affiliation: Focus Technologies, Inc., 13665 Dulles Technology Drive, Suite 200, Herndon, VA 20171, USA.
authors.forename: Daniel F
authors.initials: DF
authors.lastname: Sahm
authors.forename: Clyde
authors.initials: C
authors.lastname: Thornsberry
authors.forename: James A
authors.initials: JA
authors.lastname: Karlowsky
mesh_terms: D000818:Animals; D016208:Databases, Factual / Q000706:statistics & numerical data* / Q000639:trends; D004352:Drug Resistance, Microbial / Q000502:physiology*; D006801:Humans; D011159:Population Surveillance / Q000379:methods*