Healthcare Decision Support Systems

 Healthcare Decision Support Systems

IT Efficiency: Ontology Programming Holds the Key

The seamless integration of knowledge and data is indispensible to today’s modern healthcare decision support systems (DSS). A healthcare organization that thoroughly what is FHIR in healthcare  understands its patients and is able to respond quickly to their needs, scores highly with them-and this has become an extremely important competitive component in today’s ever-more interconnected world where patient feedback can positively or negatively affect an organization’s reputation and bottom line.

The patient care world is complex, with various information systems being utilized to streamline and automate patient care processes.Fortunately, there is a new approach to IT efficiency vis-a-vis ontological engineering-or ontology programming-that is possibly the most significant benefit to ensuring accurate data integration, which fosters a better understanding of patient needs, thus resulting in better patient care and excellent patient outcomes.

Ontological engineering excels at extracting knowledge and critical information from the various information systems within a healthcare decision support system (or its organizational databases). Ontology programming reduces often difficult data integration issues and promotes data reuse, data sharing, and common vocabularies between the information systems, from patient intake to patient discharge.

For healthcare organizations to understand their patients better, data across the entire organization or spectrum of information systems involved in patient care must to be analyzed. Knowledge from different areas or “domains” (e.g., the patient-entry process domain, hospitalization and treatment domains, and billing and insurance domains) must to be extracted in order to accurately interpret quality of care.

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