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Dr Stout Healthcare Analytics

Presented at Predictive Analytics Innovation Summit, Chicago 2017 #PAChicago https://theinnovationenterprise.com/summits/predictive-analytics-innovation-summit-chicago-2017/speakers This presentation centers on currently published findings focused on the use of predictive analytics in healthcare venues of sports medicine and orthopedic rehabilitative settings. Aspects of data access via national patient registries as well as nascent applications of machine learning will also be covered. An example of one approach of incorporating a model of assessment, evidence-based practice, treatment augmentation, and resultant outcome evaluation will be provided as well. Please be in touch http://DrChrisStout.com

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Dr Stout Healthcare Analytics

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  1. Harnessing Big Data and Analytics in Healthcare Chris Stout, PhD VP, Department of Research and Data Analytics ATI Chris Stout, PhD The College of Medicine, University of Illinois at Chicago Holdings, and VP, Department of Research and Data Analytics, ATI College of Medicine, University of Illinois, Chicago

  2. Who is in the audience today…? CIO…? CTO…? CISO….? Founder…? Investor/PE/VC….? Anyone else….? Folks that just like to raise their hands…?

  3. Machine Learning and the Profession of Medicine Feb 2016

  4. Machine Learning… not so fast…

  5. Precision Medicine Initiative®

  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.

  7. There’s an app for that… and how!

  8. There’s an app for that… and how!

  9. There’s an app for that… and how!

  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

  11. Harnessing diverse data, and a lot of it

  12. Predictive Analytics

  13. Predictive Analytics

  14. >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…

  15. 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

  16. 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!

  17. Surgeon’s Perspective on a Good Outcome • No anesthesia issues • No surprises during or after • No complications • Good wound healing • No post-op infection

  18. 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?

  19. PRN Tx Guideline PRN Tx Guideline Consult ( Consult (brought to you brought to you by your EMR) ) by your EMR

  20. I was always frustrated with the disconnect of getting evidence-based practice in real-time to the clinician while with the patient

  21. So I did some experimenting….

  22. And we may have cracked the code

  23. Combing Evidence with Practical Application, in Real-time

  24. Evidence-based practice is sort of like MoneyBall

  25. Evidence-based practice is not…

  26. Evidence-based practice is not…

  27. No longer a problem of too little data… …but too much

  28. OK, So, now WHAT?

  29. It’s about tools…

  30. Registries to the Rescue!

  31. ATI Outcomes Registry 36

  32. Collaborative Opportunities 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 37

  33. Registry in Differentiation and Exposure 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 38

  34. We are in the midst of some wonderfully revolutionalry and promising changes afoot…

  35. Please be in touch Chris.Stout@ATIPT.com or visit DrChrisStout.com for these slides

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