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ensure accuracy. Patient Safety: Achieving a New Standard for
Care In addition to ADEs, automated surveillance approaches have
proven to be effective in identifying nosocomial infections and
falls (Bates et al., 2003), although these approaches are not
used routinely. Evans et al. (1986) demonstrated that
computerized surveillance is at least as effective as
traditional surveillance methods used by infection control
practitioners for identifying hospital-acquired infections.
Natural language processing was used to search radiology reports
for indications that a patient fall after the second day of
hospitalization was a reason for the radiological examination
(Bates et al., 2003). Although there has been considerable
success in using automated surveillance techniques for detecting
certain types of adverse events, there will contin