A systematic literature review of automated clinical coding and classification systems.
Clinical coding and classification processes transform natural language descriptions in clinical text into data that can subsequently be used for clinical care, research, and other purposes. This systematic literature review examined studies that evaluated all types of automated coding and classification systems to determine the performance of such systems. Studies indexed in Medline or other relevant databases prior to March 2009 were considered. The 113 studies included in this review show that automated tools exist for a variety of coding and classification purposes, focus on various healthcare specialties, and handle a wide variety of clinical document types. Automated coding and classification systems themselves are not generalizable, nor are the results of the studies evaluating them. Published research shows these systems hold promise, but these data must be considered in context, with performance relative to the complexity of the task and the desired outcome.
American Health Information Management Association, Chicago, Illinois, USA. mary.stanfill@ahima.org
Mary H
MH
Stanfill
Margaret
M
Williams
Susan H
SH
Fenton
Robert A
RA
Jenders
William R
WR
Hersh
D001331:Automation; D002965:Classification; D059019:Clinical Coding; D006801:Humans; D018875:Vocabulary, Controlled