Data Driven Care: The Key to Accountable Care Delivery from a Physician Group Perspective

1. Data Driven Care: The Key to Accountable Care Delivery from a Physician Group Perspective Dr. Greg Spencer & Luke Skelley

2. ® Today’s Agenda • Why a regional physician group is heavily investing in analytics and data warehousing • Crystal Run Healthcare’s strategy to turn data into improved care as well as financial viability in the future • How Crystal Run manages across its patient population who are covered by 24 payer entities • Some of the preliminary challenges and successes engaging clinicians in the use of data • The importance of an adaptive data architecture to turn clinician questions into actionable results

3. ® POLL QUESTION #1What best describes the group you belong to?Health PlanPhysician GroupProvider OrganizationVendorOther

4. ® Crystal Run Healthcare • Physician owned MSG in NY State, founded 1996 • 300+providers, 16 locations • Joint Venture ASC, Urgent Care, Diagnostic Imaging, Sleep Center, High Complexity Lab, Pathology • Early adopter EHR (NextGen®) 1999 • Accredited by Joint Commission 2006 • Level 3 NCQA PCMH Recognition 2009, 2012

5. ® Crystal Run Healthcare • Single entity ACO • April 2012: MSSP participant • December 2012: NCQA ACO Accreditation • 25,000 commercial lives at risk • MSSP • 10,400 attributed beneficiaries • 82% primary care services within ACO

6. ® Crystal Run Healthcare • The mission of Crystal Run Healthcareis to improve the qualityand availabilityof, and satisfactionwith, health care services in the communities we serve. To accomplish this goal, the practice emphasizes both traditional medical excellence as well as responsiveness to consumer needs through service excellence and patient empowerment.

7. ® The Goal: The Triple Aim • Improve the health of the population • Enhance the patient experience of care • Reduce, or at least control, the per capita cost of care

8. ® Crystal Run Strategy and Objectives • Embrace goals of Triple Aim • Physicians play a crucial role in driving change in healthcare • Focus on providing coordinated care • Population health management is critical • Competition from hospitals and health plans is occurring • Coverage area is expanding, and needs to expand further • Physicians and their teams need to work together for the best of their patients • A strategic pillar is to be the practice of choice for physicians, patients, and employees

9. ® Crystal Run Governance Model joint clinical and financial governance model • Establish data warehouse priorities • Set policies for data access, information security and privacy • Develop process for setting data definitions and standards • Coordinate with Partners eCare leadership Hal Teitelbaum, MD, JD, MBA Managing Partner & CEO edw executive sponsors Greg Spencer, MD Chief Medical & Chief Medical Info Officer Michelle A. Koury, MD Chief Operating Officer Mary DeFreitas Chief HR Officer Erlene Washington Senior VP of Finance & Accounting edw governance Jonathan Nasser, MD Medical Director Greg Spencer, MD CMO & CMIO Miguel HernandezTechnology Director Lou Cervone BI Director EDW Steering Committee

10. ® Crystal Run Care Management Strategies • Embedding Care Managers at different offices, medical homes and hospitals • Identify high-risk patients from registries and PCP/ team referral • Implement evidence based protocols • Use EHR and mobile / home devices

11. ® Crystal Run Quality Structure 27 divisions each headed by its own physician specialist Manage quality efforts and information Work with Best Practice Council (quality committee) to define registries Report to practice-level committee for quality and patient safety

12. ® Why Crystal Run is heavily investing in analytics and data warehousing

13. ® POLL QUESTION #2If you are a health plan, physician group, or provider organization, do you currently exchange clinical and claims data with these other constituents?

14. ® Crystal Run Data Analytics Strategy • Implementing formal quality improvement methodology • Implementing EDW with multiple data sources • Implementing analytical applications • Daily financial reporting • Order tracking: In-house vs. Sent out • Claims Data Integration • RVUs Standardization

15. ® Crystal Run Analytics Current State • Quality improvements heavily dependent upon data • Using simple analytical tools – Excel, Access, Tableau • Time and effort spent on manual data entry and extraction is excessive and poorly scalable • Decisions about what data to use based on amount of disruption vs. value • Data entry/analysis not done at Top of Licensure • Reporting quality metrics resource intensive – kept it simple

16. ® Physician Dashboard

17. ® Physician Dashboard

18. ® Turning data into improved care & ensuring financial viability in the future

19. ® Physician Variation Analysis Mean Cost per Case = $20,000 Dr. J. 15 Cases $60,000 Avg. Cost Per Case $40,000 x 15 cases = $600,000 opportunity Total Opportunity = $600,000 $35,000 x 25 cases = $875,000 opportunity Total Opportunity = $1,475,000 Total Opportunity = $2,360,000 Total Opportunity = $3,960,000 Cost Per Case, Vascular Procedures

20. ® Crystal Run Results • Reduced hospital admissions 4+% in one year • Improved mammogram rates from 60-65% to greater than 75% • Achieved less than 9% rate of A1Cs > 9 • Blood pressure control in hypertensive patients improved to greater than 75%.

21. ® ImprovedQualityBreast Cancer Screening Mammography

22. ® Outcomes: Avoidable Admissions Monthly Quality Trend # Avoidable Admissions 17%

23. ® Outcomes: Readmissions 30 Day Readmission Rate for Medicare

24. ® Total cost difference (equalized as cost per patient treated) PEG-filgrastim use in Breast cancer patients 2012 pre-pathway 791 patients $595,920 2013 post-pathway 817 patients $368,160 TOTAL COST SAVINGS $227, 760

25. ® Reducing Pharmaceutical Costs PEG Filgrastrim cost per patient before and after breast cancer pathway

26. ® A Culture Of Efficiency: Improving Access • 41,823 fewer visits • 30,206 more patients • “Created” 12 physicians

27. ® Variation ReductionSpreadReduction in Charges

28. ® Variation ReductionSpreadImproving Access

29. ® Managing patient populations across payer entities

30. ® Crystal Run’s payer mix • 24 Payer Entities • No dominant payer, so little to no leverage for discounts, etc. • No dominant payer, so payers need to contract with Crystal Run to effectively do business in the area • Complicates data analysis due to limited population/statistics by payer

31. ® Payer Challenges • Having data-focused payer conversations about shared savings • Need claims data to support risk contracting • Multiple payers limits ability to do valid statistical modeling • Collaborating with multiple plans to develop shared savings model

32. ® Living in Two Worlds • Improvements in quality reduces costs to benefit of payer • Reduction in patient visits offset by increase in patient volume • Hospitals acquisition of physicians not based on value but to protect referrals • Triple Aim is a threat to hospitals • Hospitals have to align optimal patient care vs. optimal reimbursement

33. ® Clinician Engagement: Challenges & Successes

34. ® Clinician Engagement • Data used in physician recruitment and retention • Data also used to support alignment and/or acquisition decisions • Sharing physician performance data helps affect behavior even if no penalty or not tied to a quality effort • Sharing physician data makes outliers come to consensus • Not all physician practices focus on value • Younger physicians sometimes avoid change more than older ones

35. ® It’s All About the Data The limitation is data. The doctors need performance data They have metrics to measure care ~ 80% of Business Intelligence’s time spent gathering versus analyzing data 90/10 of data capture time to analysis time.

36. ® Crystal Run EDW Requirements • Fast to implement and fast to ROI • Capable of easily expanding to add new data sources • Library of analytical applications • Vendor with healthcare experience and expertise • Data model conducive to healthcare data • Ability to become self sufficient • Long term business partner

37. ® Adaptive Data Architecture: Turning clinician questions into actionable results

38. ® Provider-Payer Collaboration Clinical data Claims data Case mix analysis Risk stratification Utilization review Prior authorizations Utilization review Care management Care gap notification Prevent readmissions Contracting Admission notification Physician profiling Physician profiling Discharge notification Regulatory measures Regulatory measures Case management Case management Evidence based guidelines Evidence based guidelines Consumer transparency Consumer transparency Wellness programs Wellness programs

39. ® Provider Payer Data Sharing Clinical data Case mix analysis Risk stratification Utilization review Prior authorizations Utilization review Care management Care gap notification Prevent readmissions Contracting Admission notification Physician profiling Physician profiling Discharge notification Regulatory measures Regulatory measures Case management Case management Claims data Evidence based guidelines Evidence based guidelines Consumer transparency Consumer transparency Wellness programs Wellness programs

40. ® Crystal Run EDW Architecture

41. ® Catalyst Apps and Claims Data Key Process Analysis Executive Dashboard Integration Tool Comorbidity Analyzer Claims Data Population Explorer Cohort Builder Readmissions Explorer

42. Driven by business and clinical need Rapid development and deployment of data sources Built incrementally (i.e., less expensive) Ownership transferred to client with technical support as needed Align with access roles and data stewardship jurisdictions Applications support Healthcare Analytics Adoption Model ® Catalyst Data Warehouse Advantages

43. ® Healthcare Analytic Adoption Model

44. ® POLL QUESTION #3On a scale of 1-5, with 5 being very advanced, how far along is your organization in using data to guide your quality and cost initiatives?

45. ® Organizational Structure Goals SENIOR EXECUTIVELEADERSHIP TEAM GUIDANCE TEAM Provides overall governance and prioritization of initiatives CONTENT ANDANALYTICSTEAM CLINICALIMPLEMENTATIONTEAM Provides steady state domain oversight WORKGROUP Supports developmentof clinical content and analytics feedback Refines Work Group output and leads implementation ENSURETHAT… • Workgroups are created with institutional priority • Appropriate leadership is engaged in prioritization • Organizational barriers between team members are removed Provides clinical forum to develop clinical content and analytics feedback

46. Organizational Teams ® Subject Matter Expert Data Capture Data Provisioning & Visualization Women & Children’s Clinical Program Guidance Team Data Analysis Pregnancy MD Lead RN SME Normal Newborn MD Lead RN SME Gynecology MD Lead RN SME Guidance Team MD lead (e.g., Pregnancy MD Lead) RN, Clinical Ops Director Pregnancy SAM Gynecology SAM Normal Newborn SAM DataArchitect Knowledge Manager Application Administrator Permanent Teams Integrated Clinical and Technical members Supports Multiple Care Process Families

47. ® Workgroup Roles DATA CAPTURE Subject MatterExpert Application Administrators (e.g., EMR Administrators, Financial System Administrators) • Acquire key data elements • Assure data quality • Integrate data capture into operational workflow Knowledge Managers Data CaptureWorkflow Analysis Data Provisioning Data Analysis DATA ANALYSIS DATA PROVISIONING Knowledge Managers Data Architects(infrastructure) • Interpret data • Discover new information in the data (data mining) • Evaluate data quality • Move data from transactional systems into the EDW • Build visualization for use by clinicians Data Architects (Analysis) Data Architects(Visualization)

48. ® Crystal Run EDW Teams • EDW data acquisition • Systems programmers • Database administrator • Clinical SME’s • EDW data architecture and integration services • BI director • Data architects • Business development • Project manager • Clinical SME’s

49. ® Catalyst Resource Deployment Installation Improvement Independence Primary owner Secondary owner Technical Director Level of Engagement Engagement Executive Support SOW#1 SOW#3 SOW#2 SOW#4 SOW#5+ EngagementTime

50. ® The Analytic Organization’s Journey