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J Am Med Inform Assoc 2006;13:508-515 doi:10.1197/jamia.M2107
  • Focus on Automated Categorization Technique
  • Research Paper

Human and Automated Coding of Rehabilitation Discharge Summaries According to the International Classification of Functioning, Disability, and Health

  1. Rita Kukafka,
  2. Michael E Bales,
  3. Ann Burkhardt,
  4. Carol Friedman
  1. Affiliations of the authors: Department of Biomedical Informatics (RK, MEB), Columbia University, New York, NY; Mailman School of Public Health (RK, CF), Columbia University, New York, NY; Department of Occupational Therapy (AB), Columbia UniversityMedical Center, New York, NY
  1. Correspondence and reprints: Rita Kukafka, DrPH, MA, Department of Biomedical Informatics, Vanderbilt Clinic, 5th Floor, 622 West 168th Street, New York, NY 10032; e-mail: <rita.kukafka{at}dbmi.columbia.edu>
  • Received 20 March 2006
  • Accepted 12 June 2006

Abstract

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.

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

Measurements 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.

Conclusion 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.

Footnotes

  • Ann Burkhardt is presently at Long Island University, Brooklyn Campus, Brooklyn, NY.

  • Support for this research was provided by the National Center on Birth Defects and Developmental Disabilities (NCBDDD), Centers for Disease Control and Prevention (CDC), United States Departmentof Health and Human Services (HHS).

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