Enhancing Clinical Practice: Creating Dynamic Medical Content in Electronic Medical Records

Electronic Medical Records (EMRs) have revolutionized healthcare by improving access to patient data and streamlining clinical workflows. However, many EMRs still follow the rigid structures of paper-based systems, which limits their potential. A more flexible, dynamic approach to medical content is essential to truly enhance clinical practice.

A Framework for Dynamic Medical Content

Dynamic medical content refers to adaptable information tailored to specific clinical contexts, such as medical specialties or diseases. This approach allows for more relevant, precise, and actionable data to be presented at the point of care. By focusing on neurosurgical content, specifically related to brain tumors, this study outlines a framework that can be applied to other specialties and conditions.
The framework begins with defining the medical specialty and mapping clinician and patient journeys. The next step is developing clinical artifacts such as assessment forms, dashboards, and order sets, which are essential for managing specific conditions. These tools must be aligned with user needs and clinical guidelines to ensure they enhance care delivery.

The Role of Standardization and Interoperability

An important aspect of this framework is the use of standardized terminologies, such as SNOMED-CT and LOINC.
These standards ensure consistency across different healthcare settings and enable interoperability between various systems.
By coding clinical concepts with these terminologies, healthcare providers can access and share information more efficiently, improving care coordination and decision-making.

Implementation and Results

The framework was successfully implemented for neurosurgery, focusing on key patient journeys related to brain tumors. The workflow includes nine phases, ranging from initial outpatient visits and diagnostic evaluations to treatment decisions and post-operative care. At each phase, content artifacts were created to support clinical decision-making, improve workflow efficiency, and enhance patient outcomes.

For example, during the diagnostic phase, a dashboard for intracranial tumor workup and an assessment form for adult brain tumors were developed. These tools provide clinicians with critical information at the right time, ensuring that decisions are based on the most accurate and up-to-date data.