Unlocking Health Insights While Protecting Data Privacy
At the heart of quality health artificial intelligence and analytics is data governance—the processes, principles, and policies that ensure that data is reliable, consistent, and secure. However, privacy and ethical concerns, data complexity, and large data gaps make data governance difficult for many health organizations. Producing reliable and action-oriented health analytics solutions demands a collaborative approach that balances privacy and security with the need for high-quality data.
Mathematica will host a virtual event on Tuesday, June 25, from noon–1 p.m. ET, to explore pressing issues and recommendations around data governance in health care, including the following:
- Patient safety considerations when using data to build health analytics models.
- The importance of data governance in communities, including what data should be kept private and what care principles can be used to protect community data.
- How to best measure and prevent bias when creating health analytics models.
Speakers
- Ngan MacDonald, director of data innovations and the Health Data Innovation Lab, Mathematica (moderator)
- Shenita Freeman, director of solutions leadership, Mathematica
- Mike Jennings, senior director of data governance and architecture, Walgreens Boots Alliance
Who Should Attend
Those involved in health analytics solutions, particularly data architecture or data governance, within federal, state, and local government agencies; academic medical centers; payers; health systems; or foundations.
