A Data Mining Approach to Characterizing Medical Code Usage Patterns View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2002-06

AUTHORS

William E. Spangler, Jerrold H. May, David P. Strum, Luis G. Vargas

ABSTRACT

This research describes a synthetic data mining approach to identifying diagnostic (ICD-9) and procedure (CPT) code usage patterns in two U.S. hospitals, with the goal of determining the adequacy and effectiveness of the current coding classification systems. We combine relative frequency measurements with measures of industry concentration borrowed from industrial economics in order to (1) ascertain the extent to which physicians utilize the available codes in classifying patients and (2) discover the factors that impinge on code usage. Our results partition the domain into areas for which the coding systems perform well and those areas for which the systems perform relatively poorly. The goal is to use this approach to understand how coding systems are used and to highlight areas for targeted improvement of the current coding systems. More... »

PAGES

255-275

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1015014402846

DOI

http://dx.doi.org/10.1023/a:1015014402846

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1010493936

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/12018612


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