Amy Abernathy, Flatiron - Stanford Big Data 2015 | Summary and Q&A

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June 12, 2015
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Stanford
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Amy Abernathy, Flatiron - Stanford Big Data 2015

TL;DR

Learning health systems use patient data to continuously improve healthcare through integration and analysis of multiple data streams.

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Questions & Answers

Q: How are learning health systems similar to rivers of data?

Learning health systems are like rivers, with individual data points acting as rivulets that come together to create a comprehensive picture of patients' health over time.

Q: What is the role of patient-level data in learning health systems?

Patient-level data is crucial in learning health systems as it helps provide context and make sense of the information. By starting with patients, the data becomes more meaningful and can be analyzed more efficiently.

Q: How can integrating different data streams improve understanding in learning health systems?

Integrating different data streams, such as electronic health records, claims data, and clinical trials data, helps put the information in context. This integration allows for a better understanding of patient data and facilitates learning and improvement in healthcare.

Q: How can patient stories contribute to the improvement of data quality?

Patient stories are vital in identifying errors and improving data quality within a learning health system. By involving clinicians and allowing them to review and provide feedback on the data, the information becomes cleaner and clearer over time.

Summary & Key Takeaways

  • Learning health systems are like rivers of data, with individual data points forming tributaries that come together to tell patients' stories.

  • Patients serve as anchors in learning health systems, with patient-level data helping to make sense of information more efficiently.

  • Integrating different data streams and putting them in context can help create a clearer understanding of patient data in a learning healthcare system.

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