On-Demand Web Seminar  Applying interoperable data to clinical risk prediction and analytics

Hosted by Health Data Management

Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry that limit adoption. Due to new data interoperability standards for electronic health records (EHRs), other options are available.

As a clinical case study, we built a scalable, web-based system to automate calculation of kidney failure risk and display clinical decision support to users in primary care practices.

In addition, this on-demand session reviews issues and techniques to prepare clinical data from any EHR for use in analytics generally across providers.

In this session, viewers will learn:

  • Architectural overview of the web-scalable analytics apps
  • Lessons in using clinical data standards
  • Challenges in data readiness for analytics and population health
  • Effectiveness of the model in predicting kidney disease
  • Importance of a technology, physician, operations partnership
Lipika Samal, MD MPH
Assistant Professor
Harvard Medical School
John D’Amore
President &
Chief Strategy Officer
Diameter Health
Mike Perkowski
Co-founder and Partner
New Reality Media LLC

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