Turn Data into Action
Jason Jones, PhD
Chief Data Scientist | Health Catalyst
In healthcare we tend to think of predictive or prescriptive model building and deployment as technical challenges. Successful adoption of these models heavily depends upon behavior change and requires more than technical accuracy. We do not put enough emphasis on the importance of change management. This disorientation leads to uneven adoption and results. While prediction algorithms abound, tools to facilitate change management remain scarce. Jason Jones, Chief Data Scientist, Health Catalyst discusses how to achieve model understanding and optimization to help you drive action and deliver better outcomes using three perspectives: functional, contextual, and operational.
- Assess how predictive or prescriptive model endeavors are more a change management challenge than a technical one
Evaluate three types of model comprehension
Translate learnings from a use case to your own organization
About the HIMSS Clinical & Business Intelligence Community
Our Community offers opportunities to obtain practical knowledge and guidance to help you turn data into action.
We share tools, resources, and best practices about data use and management solutions that are efficient, effective and measurable. Together we can help our healthcare organizations sustain business healthy while delivering quality patient care.
Engage with peers and industry leaders through virtual learning sessions. Share your knowledge, ideas, and thoughts through monthly interactive webinars and social media engagement.
Join the Community and be a part of the movement Turn Data into Action.
[Steps to join: Clink on the previous link | Click on "Edit Participations" | Check the “Clinical & Business Intelligence Community” box | Click "Save"]
The community convenes virtually most 4th Thursdays of the month from 1:00-2:00 pm ET.