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An Automated ICD-10 Code Assigning System using A Classification Method
Author(s)
Singto, Chanida
Date Issued
January 1, 2021
Type
Conference Paper
Abstract
At present, some hospitals in Thailand have to manually analyze patient treatment data for assigning the disease diagnostic code, or ICD-10 (International Classification of Diseases and Related Health Problem 10th Revision) code. The ICD-10 codes are collected and submitted to the Ministry of Public Health to collect Thailand's disease incidence statistics and allocate a budget for the development of the country's health system. These hospitals have difficulty recruiting personnel with expertise in analyzed and assigned ICD-10 codes, causing a long working time and a problem with the accuracy of the analyzed and assigned ICD-10 codes, due to many patients daily. This paper presents the automated ICD-10 code assigning system developed for solving the problem of analyzing and assigning the ICD-10 code manually by a human expert in the hospitals. The system uses a classification method with a decision tree diagram as the model to classify the ICD-10 codes from patient treatment data, i.e., medicine and laboratory results. The system can be used as a tool to support a medical staff who is the expertise that analyzes and assigns the ICD-10 code in a more accurate and rapid manner. The evaluation of the classification result with the decision tree model is found to be 91.67 percent accurate in performance for the ICD-10 codes assigned.
Citation
Bmeicon 2021 13th Biomedical Engineering International Conference, 2021