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Healthcare data exchange faces persistent gaps in care. Knowledge graphs provide a flexible information architecture to improve interoperability, safety, and patient-centered care by enabling semantic linkage and longitudinal reasoning.

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Area of Science:

  • Health Informatics
  • Information Architecture
  • Clinical Data Management

Background:

  • Despite increased healthcare data exchange, critical care gaps persist, including missed referrals, polypharmacy risks, and continuity issues.
  • Existing information architectures struggle to represent the dynamic, multi-domain, and intent-driven nature of patient care.
  • Empirical failures in primary care (scheduling, referrals, labs, medications) and broader care lapses highlight the need for improved data representation.

Purpose of the Study:

  • To identify the information architecture requirements for representing patient care as a dynamic, multi-domain, intent-driven process.
  • To evaluate candidate architectures based on empirical failure modes and derived functional and technical requirements.
  • To determine if knowledge graphs can address the limitations of current healthcare data exchange systems.

Main Methods:

  • Analysis of empirical failure modes in Canadian primary care (appointment scheduling, referrals, labs, medication processes).
  • Identification of functional and technical requirements for an ideal healthcare information architecture.
  • Evaluation of four candidate architectures against the derived requirements, focusing on semantic linkage, schema flexibility, state tracking, longitudinal reasoning, and explainability.

Main Results:

  • Knowledge graphs uniquely satisfy the requirements for semantic linkage, schema flexibility, state tracking, longitudinal reasoning, and explainability.
  • Other evaluated architectures failed to meet the comprehensive set of functional and technical requirements.
  • Knowledge graphs demonstrate a strong potential for overcoming current data exchange limitations.

Conclusions:

  • Knowledge graphs present a promising solution for achieving truly interoperable, safe, and patient-centered healthcare.
  • Addressing regulatory, governance, and vendor implications is crucial for the successful adoption of knowledge graphs in healthcare.
  • Implementing knowledge graphs can significantly enhance the representation and management of dynamic patient care processes.