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

INTRODUCTION

Clinical decision support science is expanding to include integration from broader and more varied data sources, diverse platforms and delivery modalities, and is responding to emerging regulatory guidelines and increased interest from industry.

OBJECTIVE

Evaluate key advances and challenges of accessing, sharing, and managing data from multiple sources for development and implementation of Clinical Decision Support (CDS) systems in 2016-2017.

METHODS

Assessment of literature and scientific conference proceedings, current and pending policy development, and review of commercial applications nationally and internationally.

RESULTS

CDS research is approaching multiple landmark points driven by commercialization interests, emerging regulatory policy, and increased public awareness. However, the availability of patient-related "Big Data" sources from genomics and mobile health, expanded privacy considerations, applications of service-based computational techniques and tools, the emergence of "app" ecosystems, and evolving patient-centric approaches reflect the distributed, complex, and uneven maturity of the CDS landscape. Nonetheless, the field of CDS is yet to mature. The lack of standards and CDS-specific policies from regulatory bodies that address the privacy and safety concerns of data and knowledge sharing to support CDS development may continue to slow down the broad CDS adoption within and across institutions.

CONCLUSION

Partnerships with Electronic Health Record and commercial CDS vendors, policy makers, standards development agencies, clinicians, and patients are needed to see CDS deployed in the evolving learning health system.