SAMS – A Systems Architecture for Developing Intelligent Health Information Systems

Abstract

In this paper, SAMS, a novel health information system architecture for developing intelligent health information systems is proposed and also some strategies for developing such systems are discussed. The systems fulfilling this architecture will be able to store electronic health records of the patients using OWL ontologies, share patient records among different hospitals and provide physicians expertise to assist them in making decisions. The system is intelligent because it is rule-based, makes use of rule-based reasoning and has the ability to learn and evolve itself. The learning capability is provided by extracting rules from previously given decisions by the physicians and then adding the extracted rules to the system. The proposed system is novel and original in all of these aspects. As a case study, a system is implemented conforming to SAMS architecture for use by dentists in the dental domain. The use of the developed system is described with a scenario. For evaluation, the developed dental information system will be used and tried by a group of dentists. The development of this system proves the applicability of SAMS architecture. By getting decision support from a system derived from this architecture, the cognitive gap between experienced and inexperienced physicians can be compensated. Thus, patient satisfaction can be achieved, inexperienced physicians are supported in decision making and the personnel can improve their knowledge. A physician can diagnose a case, which he/she has never diagnosed before, using this system. With the help of this system, it will be possible to store general domain knowledge in this system and the personnel's need to medical guideline documents will be reduced.

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“…About 37% of our study participants mentioned that this system could improve patient satisfaction at a moderate level. This finding is congruent with the results of Yilmaz's study that investigated the use of an architectural system for the development of smart information systems [28].…”

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“…[8], [9], reveal that there are a large number of CDSSs in very different healthcare domains. Some are proposals of generic frameworks that could be used for the diagnosis and treatment of different pathologies [9]- [11]. However, the majority of the approaches focus on ad hoc systems developed for specific application domains [12]- [15].…”

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“…Ontologies and their formal description logics can provide intelligent solutions for the problem. Ontologies are superior to relational databases and taxonomies in terms of expressiveness [109]. They support knowledge sharing, reuse, and inference.…”

“…They support knowledge sharing, reuse, and inference. Yilmaz et al [109] proposed an architecture for developing intelligent EHR systems. It stores data using OWL ontologies and supports sharing of data between different hospitals.…”