- Mike Jude, Digital Health Research Manager, Frost & Sullivan.
Source: Olive AI, August 6, 2019
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Getting to the Wrong Answer Faster with Your Analytics: Shifting to a Better Use of AI in HealthcareWrong conclusions in your analytics can cause waste and disillusionment, not to mention suboptimal outcomes that may take months or even years to recover from. But analytic analysis isn’t about perfection—it’s about getting to the right answer by quickly getting to the wrong one. In this interactive webinar, Jason Jones, chief data scientist at Health Catalyst, walks through scenarios that illustrate how commonly used analytic methods can lead analysts and leaders to the wrong conclusions, and shares how to course correct if this happens to you. |
Society of Actuaries: Biggest Challenge to Implementing Predictive Analytics in the Next 5 Years, per Survey of Healthcare Execs
1. Lack of skilled employees: 13%
2.
Regulatory issues (e.g. HIPAA): 12%
3. Too much data: 12%
4.
Incomplete data: 11%
5. Lack of sufficient technology: 11%
6. Lack
of budget: 10%
7. Lack of confidence in its accuracy: 8%
8. My
organization won't face any barriers: 7%
9. Patient matching: 6%
10. Lack of executive support: 5%
11. Don't know/not sure: 5%
12.
My organization won't be implementing predictive analytics in the next 5
years: 0%
13. Other: 0%.
Source:
Society of Actuaries
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