Human and automated coding of rehabilitation discharge summaries according to the International Classification of Functioning, Disability, and Health.
OBJECTIVE
The International Classification of Functioning, Disability, and Health (ICF) is designed to provide a common language and framework for describing health and health-related states. The goal of this research was to investigate human and automated coding of functional status information using the ICF framework.


METHODS
The authors extended an existing natural language processing (NLP) system to encode rehabilitation discharge summaries according to the ICF.


METHODS
The authors conducted a formal evaluation, comparing the coding performed by expert coders, non-expert coders, and the NLP system.


RESULTS
Automated coding can be used to assign codes using the ICF, with results similar to those obtained by human coders, at least for the selection of ICF code and assignment of the performance qualifier. Coders achieved high agreement on ICF code assignment.


CONCLUSIONS
This research is a key next step in the development of the ICF as a sensitive and universal classification of functional status information. It is worthwhile to continue to investigate automated ICF coding.
Kukafka
Rita
R
Department of Biomedical Informatics, Vanderbilt Clinic, New York, NY 10032, USA. rita.kukafka@dbmi.columbia.edu
Bales
Michael E
ME
Burkhardt
Ann
A
Friedman
Carol
C
D000203:Activities of Daily Living / Q000145:classification*; D004185:Disability Evaluation; D001330:Electronic Data Processing; D005568:Forms and Records Control; D006304:Health Status; D006305:Health Status Indicators; D006801:Humans; D009323:Natural Language Processing; D010351:Patient Discharge; D012372:ROC Curve; D018875:Vocabulary, Controlled