Healthcare Data Model Challenges

Healthcare Data – Healthcare data is too complicated, fragmented, and difficult to model within a unified data analytics model.

EMR Issues – Most existing EHR/EMR systems are not designed with usability and clinical workflow in mind. As a result, these systems become obstacles for physicians and their patients, forcing physicians to work outside of working hours to complete documentation. Traditional EMR systems have limited or no decision support features to assist physicians/doctors in their assessment and clinical process.

System Interoperability – The seamless, effective, and meaningful exchange of patient information is yet to be achieved across healthcare systems. The existing EMR systems do not use open standards, making it difficult for patients and clinics to integrate medical records from multiple sources, resulting in unnecessary tests and delayed diagnoses.

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