An Ontology-Based Medical Information Management System for Electronic Claim Processing Systems

Background The electronic claim processing (ECP) systems in healthcare insurance require, naturally, comprehensive, and secure management of medical information. Even though the state of the art ECP systems can read the payment rules written in plain-text, there are hundreds of rules (each including tens of conditions) in a conventional ECP system. The conditions of the rules, in turn, refer to thousands of medical entities and concepts. Although domain experts can manage the plain-text payment rules, the length and complexity of the rules yield a lack of understandability and an increase in-rule and inter-rule inconsistencies. Hence, a more efficient and straightforward system is required. This study aims to make the medical data bank that is used for the claim management system more efficient by using ontology. Method We proposed ontology- based on the medical information management system (ONTMIMS) in healthcare insurance- to simplify the payment rules. 1,312 sets of diagnosis and health services are included in ONTMIMS. The development of the ontology compromises four stages: i) specification and conceptualization; ii) formalization; iii) implementation; and, iv) evaluation. Protégé and Apache Jena library are conducted as tools, and the ONTMIMS is used in a real-life ECP system. Results The experiments indicated that ONTMIMS increased the understandability from 35.1% to 64.9%. Distinguishing in-rule inconsistencies increased from 65% to 82.5%, and distinguishing inter-rule inconsistencies increased from 78.8% to 85%. Conclusions Ontology, as in many other studies, is very useful in representing and processing information. That is the first study using ontology in ECP systems used in health insurance institutions. The results showed that ontology increased the in-rule and inter-rule consistency and made the rule sentences more understandable by the domain experts.