An Ontology-Based Medical Information Management System for Electronic Claim Processing Systems
Abstract Background: Electronic claim processing (ECP) systems in healthcare insurance require comprehensive and secure management of medical information. Even though state of the art ECP systems can read payment rules written in plain-text, there are hundreds of rules (each including dozens 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 plain-text payment rules, the length and complexity of the rules yield low comprehensibility and in-rule and inter-rule consistencies. Hence, a more efficient and straightforward system is required. This study aims to make a claim management system medical data bank more efficient using ontology. Method: We developed an ontology-based medical information management system (ONTMIMS) in healthcare insurance to simplify payment rules. 1,312 sets of diagnosis and health services were included in the ONTMIMS. The development of the ontology was compromised of four stages: i) specification and conceptualization; ii) formalization; iii) implementation; and iv) evaluation. Protégé and Apache Jena library tools were used to execute queries on the ontologies and the ONTMIMS was tested on an active ECP system. Results: The experiments indicated that ONTMIMS increased comprehensibility rates for domain experts 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. This is the first study applying ontology to ECP systems for health insurance institutions. The results demonstrate that applying ontology increased in-rule and inter-rule consistency and made rule sentences more comprehensible to domain experts.