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Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
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Enhancing Clinical Practice: Creating Dynamic Medical Content in Electronic Medical Records.

Mobin Yasini1, Dennis Rausch1, Irina Kozinova1

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Summary
This summary is machine-generated.

This study introduces a framework for dynamic Electronic Medical Records (EMR) content tailored to clinical context, improving information access and workflows. The developed neurosurgical content demonstrates user needs and clinical relevance.

Keywords:
Health Information InteroperabilityMedical recordProblem-oriented

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Area of Science:

  • Health Informatics
  • Medical Software Development
  • Clinical Workflow Optimization

Background:

  • Electronic Medical Records (EMRs) have limitations inherited from paper-based systems.
  • Lack of context-specific dynamic content hinders efficient clinical information retrieval.
  • Need for adaptable EMR content tailored to medical specialty and disease.

Purpose of the Study:

  • To propose and validate a framework for developing dynamic, context-aware medical content within EMRs.
  • To improve information accessibility, streamline clinical workflows, and enhance patient care through tailored content.
  • To demonstrate the framework's applicability by developing neurosurgical content for brain tumors.

Main Methods:

  • Defined a framework involving medical specialty identification and user journey mapping.
  • Iteratively developed clinical artifacts such as assessment forms, dashboards, and order sets.
  • Utilized standardized terminologies to ensure content consistency and interoperability.

Main Results:

  • Successfully developed dynamic neurosurgical content aligned with user needs and clinical relevance.
  • The framework facilitated the creation of context-specific EMR content.
  • Demonstrated the potential for improved information access and workflow efficiency.

Conclusions:

  • The proposed framework enables the development of dynamic, context-specific EMR content.
  • Tailored content shows promise for enhancing clinical practice and patient outcomes.
  • Future work should explore scalability, AI integration, and quantitative impact assessment.