1. #HASummit14 Session #12: Sneak Peek: Improving Patient Engagement and Outcomes with Predictive Analytics Pre-Session Poll Question Does your organization currently share predictive analytic results with patients? a)Yes b)No c)Unsure or not applicable Lou Cervone Director of Business Intelligence Crystal Run Healthcare Gregory Spencer, MD Chief Medical Officer Crystal Run Healthcare

2. #HASummit14 Our Organization  Physician-owned MSG in NY State, founded 1996  350+ providers, 30+ locations  40,000 commercial lives at risk  12,000 attributed beneficiaries  Joint Venture ASC, Urgent Care, Diagnostic Imaging, Sleep Center, High Complexity Lab, Pathology  Early adopter EMR (NextGen®)  Accredited by Joint Commission  Level 3 NCQA PCMH Recognition 2

3. #HASummit14 The Pain Point 3 How can we leverage the capabilities of our analytics platform to better engage and activate patients? Can existing data be used interactively to help modify patient behavior?

4. #HASummit14 The Concept of a Flight Path Example Diabetes Cohort Good Profile Poor Profile 1.A1c < 7 2.LDL < 100 3.BP < 130/80 1.A1c > 7 2.LDL > 100 3.BP > 130/80 $ COST per member per year (charges) For > 1 year of encounters (disease specific) (5 years, 26k patients) 4

5. #HASummit14 Poll Question #2 How are you currently engaging patients using data? a)We actively use predictive analytics with patients to show them the predicted impact of their lifestyle choices b)We share lab values and results with patients and verbally counsel them on long-term health implications of lifestyle choices c)We share results only d)Unsure or not applicable 5

6. #HASummit14 Our Approach And Results 6

7. #HASummit14 Our Goal 7 Using disease-specific: metrics, costs, analytics, simulation, and predicted outcomes… to engage both the patient and clinician in more efficient diabetes care. Our Approach

8. #HASummit14 What factors can predict “health”? Lab ValuesComplicationsRisk Scores Family HistorySubstance UseDemographics 10

9. #HASummit14 Flight Path – Risk Risk Prediction Given everything we know about the patient, what is his expected “risk score”? “What-if” analyses Sliders will show how changing X (e.g., BMI) will affect the overall risk score 9

10. #HASummit14 Flight Path – Future complications 10 Predict the likelihood of developing one of 14 diabetes- related complications and display the “next most likely” Possible complications Ranked by “next likely” Cataracts Coronary Artery Disease Diabetic Ketoacidosis Diabetic Retinopathy End Stage Renal Disease Glaucoma Peripheral Neuropathy

11. #HASummit14 Flight Path – Recommendations 11 Compile list of recommendations for each complication Calculate recommendation score Sort recommendations from highest to lowest Present in both a patient view and clinician view Likelihood of developing complication Complication Severity Recommend Impact Recommend Score

12. #HASummit14 Flight Path – Recommendations 12 Categorize recommendations by type/theme to facilitate patient’s ability to process and remember

13. #HASummit14 Leveraging Predictive Layers 11

14. #HASummit14 Poll Question #3 Based on what you’ve seen, is this something you could envision implementing in your organization? a)Yes b)No c)Unsure or not applicable 13

15. #HASummit14 Expected Results/Measurable Analytics 14 Gain patient understanding of the life choices and things within their control that can impact their potential clinical outcomes Show measurable improvement in patient engagement and clinical outcomes Inform future application development

16. #HASummit14 Future Plans Deploy application into clinical areas o Endocrinology, primary care o Diabetic nurse educator Evaluate effectiveness o Follow the cohort that has used the tool o Follow cost, Hemoglobin A1c, quality measure compliance o Patient Activation Measure (PAM)? Begin work on heart failure and subsequent additional applications 15

17. #HASummit14 Lessons Learned 1.Select your clinical conditions carefully 2.What you learn informs future applications and saves time 3.Manage the data 4.Decide on time parameters and how to treat values over time 5.Consider how the data is to be displayed for best effect 16

18. #HASummit14 Analytic Insights A Questions & Answers 18

19. #HASummit14 Choose one thing… Write down one thing will you do differently after hearing this presentation 19

20. #HASummit14 Thank You 20

21. #HASummit14 21 Session Feedback Survey 1.On a scale of 1-5, how satisfied were you overall with this session? 1)Not at all satisfied 2)Somewhat satisfied 3)Moderately satisfied 4)Very satisfied 5)Extremely satisfied 2.What feedback or suggestions do you have?

22. #HASummit14 Upcoming Speakers 3:45 PM – 4:35 PM 16)Delivering Excellence at Stanford Health Care Amir Dan Rubin, President and CEO, Stanford Health Care 4:35 PM – 5:00 PM 17)The Future World of Value-Based Healthcare (Documentary featuring Michael Porter) Caleb Stowell, MD, Vice President, Research and Development, International Consortium for Health Outcomes Measurement (ICHOM, Senior Researcher, Harvard Business School) 22 Location Grand Ballroom