Electronic Health Record Error Prevention Approach Using Ontology in Big Data

Electronic Health Record (EHR) systems have been playing a dramatically important role in tele-health domains. One of the major benefits of using EHR systems is assisting physicians to gain patients´ healthcare information and shorten the process of the medical decision making. However, physicians´ inputs still have a great impact on making decisions that cannot be checked by EHR systems. This consequence can be influenced by human behaviors or physicians´ knowledge structures. An efficient approach of alerting to the unusual decisions is an urgent requirement for current EHR systems. This paper proposes a schema using ontology in big data to generate an alerting mechanism to assist physicians to make a proper medical diagnosis. The proposed model is Ontology-based EHR Error Prevention Model (OEHR-EPM), which is implemented by a proposed algorithm, Error Prevention Adjustment Algorithm (EPAA). The ontological approach uses Protege to represent the knowledge-based ontology. The proposed schema has been examined by our experiments and the experimental results show that our schema has a higher-level accuracy rate and acceptable operating time performance.