Data governance is crucial to the implementation of AI but often doesn’t get the focus it deserves. A strong data governance strategy must be specified clearly and for the complete data lifecycle. It must also be conducive to clinical and research workflows so that it ethically improves quality and patient outcomes.
On this episode of Diagnosing Healthtech, Mike Sanky, Global Industry Lead of Healthcare & Life Sciences at Databricks, joins us to discuss:
- The role of data governance in establishing and maintaining trust with patients and clinicians.
- How to proactively address risks and navigate the complexity of the regulatory landscape in AI implementation.
- Common mistakes teams can make in securing AI usage and deployment throughout the data lifecycle.
- The crucial components to keep in mind when building a data governance framework.
- The unique barriers to democratizing data in healthcare.
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