1. Bringing Advanced Analytics to Healthcare
Practical Insights
Gwen O’Keefe, MD
Faculty, International Institute for Analytics

2. We’ve Digitized Healthcare
Now What?
We are going to talk about what you need to know to lead or participate in analytics efforts using predictive analytics; how to assess whether things you are being sold are really going to benefit your organization; how you can understand this rapidly changing world; get excited about what we might be able to do!
We haven’t scratched the surface of using all the information we have today – sensors, pumps, wearables, all add to the standard data we are used to dealing with in the EMR.

3. What's the hype about?
Machine learning, artificial intelligence, prescriptive analytics…

4. What is Predictive analytics?
Predictive analytics is the branch of the advanced analytics which is used to make predictions about unknown future events. Predictive analytics uses many techniques from data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about future.
Key things to know:
Enabled by advances in technology and infrastrucutre, as well as in statistics and mathematics
New techniques allow use of 100s to 1000s variables, process massive quantities of data
Models have to learn on data – so if there is not a data set, and a defined end point, models will not be able to learn
Lots of hype and almost a feeling like its “magic”
What is Predictive Analytics? - Predictive Analytics Today

5. Predictive Analytics in Industry
Entertainment: Netflix
What movies will you like?
Shopping: Amazon
If you like this, you might also like this…
Sports: Oakland A’s…
Moneyball
Automotive: Ford, GM…
Predictive maintenance
Self-driving cars - predictive collision avoidance
Prescriptive analytics – automation – in healthcare still need to have a human in the mix

6. Healthcare Hype, and Anxiety
Purpose built analytics
New platforms
Will doctors be replaced?
Personalized medicine
Lots of Hype, and Anxiety in healthcare
Optum, others around for long time
New entrants – KenSci local, Dato, GNS, ….
Radiology

7. Unfair Advantage?
Many think advanced analytics and technologies give organizations an unfair advantage

8. Help your organization keep up
Don’t want to be left behind. How are you going to help your organization . Even smaller groups can take advantage of this in a disciplined way. Someimes it seems like large orgs just have an easier time spending lots of money on speculative trials
Pay close attention and be a fast follower

9. What is your organization used to?
Analytics maturity - where is your organization?
Has the problem been measured in the past?
Machine learning models are hard to explain - are your customers prepared to accept this?
Do you need to start with descriptive statistics before moving into more sophisticated models

11. What are the basics for success?
Understanding of the problems to be solved
Data and infrastructure
Operational planning and process to incorporate
What's the story line you are hoping to change?

12. Common focus areas Risk for readmission End of Life
Risk of disease progression
Sepsis
High cost patients/members
Preterm birth

13. Unintended consequences
Example: End of life modeling for care management and hospice
What is the goal?
Distribute same # of resources more effectively?
Decrease need for staff?
Increase # of patients
Get people into the program earlier
Is there a plan to take action, get the money or staff needed, develop a program, etc?
Who owns accountability for the results?
How will it be measured?

14. Beyond EMR and claims data
Geocoded data
Genomics
Patient reported data
Public census data

15. What's your role in all this?
Data management?
Infrastructure?
push back on assumptions the technology itself has to cost a lot (storage is cheap, it's the other stuff that gets pricey - people and time)
Analysis and story telling?

16. Data Swamp Or
Data Lake

17. It all starts with understanding the problems and listening
You will be MUCH more successful if you truly understand what the questions are, and what having new information will do to enable change. Don’t waste time on problems where there is no desire to change, or where new information is not going to change an outcome

18. Educate Yourself Tom Davenport’s books
Competing on Analytics
Analytics at Work
Keeping up with the Quants
Measure something in your own work
Ask questions

19. Summary Assess where you are today
Pick problems with adequate data, workflow, process and ownership
Learn as much as you can
Tell the story in a way people can identify with