Original Article
Automatic Selection of Diagnosis Procedure Combination Codes Based on Partial Treatment Data Relative to the Number of Hospitalization Days
Author(s):
Kazuya Okamoto*, Toshio Uchiyama, Tadamasa Takemura, Naoto Kume, Tomohiro Kuroda and Hiroyuki Yoshihara
Objectives: The authors developed and evaluated a method of selecting accurate diagnosis procedure combination (DPC) codes based on standardized treatment information relative to the number of hospitalization days.
Methods: The authors used machine learning methods to generate DPC codes based on treatment data. The machine learning methods utilized were the Naïve Bayes method, the SVM method, and a combined method of the two methods. We prepared DPC code data and standardized treatment data corresponding to cases occurring in fiscal year 2008 at Kyoto University Hospital. To produce classification models, machine learning methods require a moderate amount of data corresponding to each DPC code; accordingly, we selected 166 DPC codes that were each related to at least 20 cases. The .. Read More»
DOI: 10.24105/ejbi.2018.14.1.8