Nazila Moftian 1 ,
Peyman Rezaei-Hachesu 1 ,
Mahsa Dehghani 1 and
Taha Samad-Soltani 2 , *
Authors Information
1 Department of Health Information technology, Tabriz University of Medical Sciences, Tabriz, Iran
2 School of Medical Informatics and Management, Tabriz University of Medical Sciences, Tabriz, Iran
* Corresponding author: Taha Samad-Soltani, School of Medical Informatics and Management, Tabriz University of Medical Sciences, Tabriz, Iran, Tel: +989129321546 [email protected]
Article information
Biotechnology and Health Sciences: February 28, 2018, 5 (1) ; e13667
Published Online : February 01, 2018
Article Type: Research Article
Received: March 12, 2017
Accepted: June 14, 2017
To Cite: Moftian N, Rezaei-Hachesu P, Dehghani M, Samad-Soltani T. Designing Automatic Coding Module of Cancer Open Text Pathology Reports Based on International Classification of Diseases for Oncology, Biotech Health Sci. 2018 ; 5(1):e13667.
Abstract
Background: In the domain of clinical documents, all diseases are classified at templates by the world health organization and specific codes have been assigned to them. The goal of this study was automatic coding of cancer free texts based on International Classification of Diseases for Oncology (ICD-O-3) and evaluation of results.
Methods : In this research, the preparation and development of one initial sample of automatic coding module on pathology reports open texts existing in PubMed’s cancer titles database is performed for exploitation of the information based on the texts related to cancer to coding the information based on ICD-O-3. After developing the algorithm for exploiting cancer phrases and the codes based on ICD-O-3 and converting them to code in programming environment, the required data for implementation and algorithm testing were performed and finally the obtained results were evaluated.
Results : Automatic coding prepares the possibility of coding and listing information inside the text and also coding the existing titles of neoplasms at descriptive text of pathology reports and with an accuracy of approximately 70%. This study explained a simple stepwise approach to coding issues in medicine.
Conclusions : It performed effectively on free texts and could be used as a decision support module in Health Information Systems to reduce coding errors.
Keywords: Clinical Coding; Informatics; Neoplasms; Pathology
© 2018, Biotechnology and Health Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.
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