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Learning to Share Health Care Data: A Brief Timeline of Influential Common Data Models and Distributed Health Data Networks in U.S. Health Care Research.

John WeeksRoy Pardee
Published in: EGEMS (Washington, DC) (2019)
The last twenty years of health care research has seen a steady stream of common health care data models implemented for multi-organization research. Each model offers a uniform interface on data from the diverse organizations that implement them, enabling the sharing of research tools and data. While the groups designing the models have had various needs and aims, and the data available has changed significantly in this time, there are nevertheless striking similarities between them. This paper traces the evolution of common data models, describing their similarities and points of departure. We believe the history of this work should be understood and preserved. The work has empowered collaborative research across competing organizations and brought together researchers from clinical practice, universities and research institutes around the planet. Understanding the eco-system of data models designed for collaborative research allows readers to evaluate where we have been, where we are going as a field, and to evaluate the utility of different models to their own work.
Keyphrases
  • healthcare
  • electronic health record
  • big data
  • public health
  • data analysis
  • machine learning
  • risk assessment
  • climate change
  • affordable care act
  • neural network