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Advances in Sharing Multi-sourced Health Data on Decision Support Science 2016-2017.

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Clinical Decision Support (CDS) systems face challenges in data integration and standardization. Partnerships are crucial for advancing CDS in the learning health system.

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Area of Science:

  • Health Informatics
  • Clinical Decision Support Systems
  • Data Science

Background:

  • Clinical decision support (CDS) science is expanding to integrate diverse data sources, platforms, and delivery methods.
  • The field is responding to new regulatory guidelines and growing industry interest.

Purpose of the Study:

  • To evaluate advances and challenges in data access, sharing, and management for CDS development and implementation (2016-2017).

Main Methods:

  • Literature and scientific conference proceedings assessment.
  • Review of current and pending policy development.
  • Analysis of national and international commercial applications.

Main Results:

  • CDS research is driven by commercialization, policy, and public awareness, but faces challenges.
  • Patient data sources (genomics, mobile health), privacy, computational tools, app ecosystems, and patient-centric approaches show uneven maturity.
  • Lack of standards and regulatory policies for data sharing hinders broad CDS adoption.

Conclusions:

  • Collaboration between EHR/CDS vendors, policymakers, standards agencies, clinicians, and patients is essential.
  • These partnerships are needed for effective CDS deployment within the learning health system.