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Using Big Data and Predictive Analytics in Healthcare
1. Using Big Data
and Predictive
Analytics in Healthcare
Chris Stout, PhD
Vice President
Clinical of Research and Data Analytics - ATI
and
The College of Medicine, University of Illinois at
Chicago
2. Who is in the audience today…?
PT students…?
PT faculty…?
Biomedical Sciences students….?
Biomedical Sciences faculty…?
Anyone else….?
Folks that just like to raise their hands…?
6. There’s an app for that… and how!
Roughly 200 new apps added
every day.
Those apps are increasingly being
used in clinical trials.
Right now, there are 860 trials
underway across the globe testing
health apps for clinical use.
If the evidence supporting some of
those apps pans out — e.g., if
they’re able to reduce ER visits or
improve medication adherence —
they could help cut health care
costs in the future.
10. Apple HealthKit
In 14 of 23 major hospitals are trialing
Google, Phillips, Samsung, IBM, and
others are getting deeper into health-
based technology applications
Healthcare + fitness apps =
comprehensive picture
Send to MD or case manager
16. >15,000 prior-managed bills were loaded and rerun
against the ODG Treatment UR Advisor for each ICD9-
CPT combination on frequency, number of visits,
recommendations from ODG Treatment, and the "Bill
Review Payment (or ODG Approval) Flags" divided
into Green, Yellow, Red…
17. Green, OK to auto-pay up to ODG Codes for
Automated Approval max number of visits;
Yellow, OK to auto-pay up to 25th %tile
number of visits
Red, need to review
18.
19.
20. It’s nice to work with workers’ comp
outcomes because…
Outcomes are VERY Quantified
– RTW at the same job description and PDL
or not?
– How many days passed before RTW?
– Nice, clean, and tidy!
21. Surgeon’s Perspective on a
Good Outcome
• No anesthesia issues
• No surprises during or after
• No complications
• Good wound healing
• No post-op infection
22. But how does the story end?
Is the patient back at work?
Quickly?
At the same PDL as prior to injury?
With the same job classification?
37. Collaborative Opportunities
37
Example Projects
Analyzing individual patient demographic,
baseline and outcomes characteristics to
predict risk for developing chronic
musculoskeletal pain
Analyzing clinic and clinician, patient
demographics, baseline and outcomes
characteristics to predict likelihoods for
appointment cancellation
38. Registry in Differentiation and Exposure
38
ATI possesses > 2 million unique cases of clinical outcomes
Solid profile describing clinical-operational results
Building towards differentiation
Creating National Benchmarks for comparison purposes
Developing models to predict and profile best care behaviors
Using data to target improvements to differentiation
Partnering with world class research institutes to innovate, improve patient
management and clinical outcomes
39.
40. We are in the midst of some
wonderfully revolutionalry and
promising changes afoot…
41.
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43.
44. Please be in touch
Chris.Stout@ATIPT.com
or visit DrChrisStout.com
for these slides