HIMSS Clinical & Business Intelligence Community of Practice. January 28, 2016

Transcription

1 HIMSS Clinical & Business Intelligence Community of Practice January 28, 2016

2 Welcome Michael Berger, PE C&BI Community Co-Chair Head of Population Health Analytics Mount Sinai Health Arthur Panov, MPH, CPHIMS C&BI Community Co-Chair HIT Architect IBM Watson Health Shelley Price, MS, FHIMSS C&BI Community Organizer Director, Payer & Life Sciences HIMSS

3 Welcome Agenda HIMSS C&BI Community Updates / Announcements Presentation & Discussion: Care Team Transformation for Population Health Management o Karen Handmaker, MPP, PCMH CCE, Vice President, Population Health Strategies, Phytel/IBM Watson Health Wrap-Up / Next Steps

4 C&BI Community Updates / Announcements

5 Agenda 3 Pillars: Education, Exhibition, Networking Education: 2 key topic areas: Care Coordination & PopHealth; C&BI Exhibition: Knowledge Centers Population Health Clinical & Business Intelligence Networking: Receptions PopHealth Reception Reception Knowledge Centers Casanova Meeting Room, Booth Tuesday, March 1, :00-7:00pm PT C&BI Community Reception Knowledge Centers Casanova Meeting Room, Booth Wednesday, March 2, :00-7:00pm PT The HIMSS Spot C&BI: Thursday, March 3, :30-10:00am PT The Digital Brochure is available now on-line.

6 Casanova Meeting Room Booth HIMSS16 C&BI and Population Health Knowledge Centers

7 C&BI & PopHealth Receptions Tuesday, March 1 & Wednesday, March 2 6:00-7:00 pm PopHealth and C&BI Knowledge Centers

8 HIMSS C&BI Community Meetup at The HIMSS Spot Thursday, March 3, :30-10:00am PT #PutData2Work DISCLAIMER: The views and opinions expressed in this presentation are those of the author and do not necessarily represent official policy or position of HIMSS.

9 Working Concept: Clinical & Business Intelligence: Getting Smart on the Top Issues and Resources to Help You Turn Data into Action Where are you on your pathway to value using clinical and business intelligence? Are you defining your current state, needs, and goals for your C&BI program? Wrapping your arms around data and organizational governance? Trying to figure out how to use and integrate your data, open data, and Big Data for your strategic goals? Endeavoring to put it all in place and employ population health management tools and strategies to bring value to your population and organization? Or do you have war stories and best practices to share? Then come to this meetup with the C&BI Committee and its groups to learn about new HIMSS tools and resources such as the population health management capabilities guide and discuss the Top 10 key C&BI issues for today and tomorrow, all to help you on your journey to Turn Data into Action. Thursday, March 3 9:30-10:00am

10 We will take questions at the end of the presentation C&BI Community Guest Speaker Please type your questions into the Q&A box.

11 Turn Data into Action: Care Team Transformation for Population Health Management HIMSS Clinical & Business Intelligence Community Karen Handmaker, MPP, PCMH CCE January 28, 2016

12 Today s Presentation Objectives: Clinical and business intelligence (C&BI) is the use and analysis of data captured in the healthcare setting to directly inform decision-making. Describe the imperative for care team transformation in the context of population health goals and new payment incentives Provide a framework on how health systems redesigning care management for population health management Offer examples of how health information technology applications enable advanced care team workflows today and what we can expect in the near future

13 Flipping Healthcare : A Sign of the Times

14 Where is Your Organization On the Journey to Value? Max risk RISK TRANSFORMATION FULL CLINICAL RISK New risk contracts fail to return significant margins without clinical transformation OPTIMAL VALUE CREATION AND VALUE CAPTURE OPTIMAL CLINICAL DELIVERY Clinical transformation allows value creation to accrue predominantly to the payer CLINICAL TRANSFORMATION Max transformation 14

15 But, Preparing for Value is a Work In Progress PHM Strategy Confirmed Mixed Financial Incentives PHM Infrastructure Evolving Front Line Not Yet Top of License Buy/Affiliate to Complete Care Continuum FFS Dominant but Shifting Multiple Systems and Data Sources to Integrate Workflows Largely Manual and Vary Across Practices Secure ACO, CIN and Direct Employer Contracts FFS Contracts Include Quality Bonuses Analytics Initially Focused on Cost and Care Gaps Actionable Data Minimal Reduce Total Cost of Care Medicare and Commercial Shared Savings Interoperability Not There Yet Focused on Tip of the Iceberg Scale PCMH Funding for Care Teams Unstable Medical Neighborhood Loosely Coordinated Patient Engagement Episodic and Visit-Centered 15

16 New Questions for Care Teams to Answer What is risk profile of my population? How do I compare to others on quality & costs? Who are my high-cost, high-risk patients? Which patients are likely to develop chronic conditions? How do I most effectively engage my population? How do I effectively manage them? How do I get paid for performance?

17 PCMH Building Blocks Designed to Build PHM Infrastructure Population Health Whole- Person/ Holistic Care Improve Patient Satisfaction Team- Based Care Reduce Health Care Costs Personal Clinician Appropriate use of HIT Quality Improvement Performance Improvement

18 Technology Must Be Intentionally Designed In LEAN & Process Design Processes Efficient Ways of Working, Scale Automation Technology PHM and Engagement EMR Analytics Training People Knowledge, Skills, Teams, Leadership, Culture

19 Bottom Up Model Drives Scale and Improvement QI Patient Engagement Enabled Care Teams Line of Sight Data Integrity

20 PCP Attribution: Is This a Process? At registration, the front desk should confirm the PCP for every patient.

21 REQUIRED: Structured Data, Sophisticated Algorithms, Real Time Reports and Behavior Change BMI and Follow Up Tobacco screening and cessation intervention Scored together

22 Key Strategies to Improve Data Quality Measures 1. Provider Attribution Consistently confirm and update PCP attribution to every patient so reports will be trusted 2. Existing Data Capture Use consistent locations in EMR for structured and scanned data (e.g., lab results, test orders, patient-reported data) 3. New Data Capture Create new structured fields rather than additional flow sheets for specific measures (e.g., fall risk assessment, Rx in care plan) 4. Eliminate Free Text Direct teams to use structured fields to collect data formerly entered as free text (e.g., tobacco cessation counseling, follow-up for positive depression screening) 5. Make Data Clean-Up Part of Standard Work Assign staff to regularly review provider attribution, invalid data entries, proper use of new workflows, etc. to enhance reliability

23 Line of Sight in Near Real Time is Essential Monitor performance measures Compare provider and care team results Use drill-down capabilities to find outliers and take action

24 We Must Go Deeper >2/3 of catastrophic patients this year were not catastrophic the previous year We must focus on patients below the waterline this year to prevent next year s catastrophic cases.

25 Is A1c>9 An Effective Stratification Factor? The majority of 9+ (65%) were not 9+ the year before. 35% moved up from a lower group. 30% were not tested. No Test 30% 9+ 35% <7 6% 7 to 9 29% Prior Year A1c Results for 9+ Patients

26 Stratify and Align Cohorts with Care Team Roles

27 Simplistic Example: Managing a Diabetes Population High-Risk (1840 Diabetics) # % Avg / PCP Missing HbA1c; High HbA1c; High BP % 73 Missing HbA1c; High HbA1c; High BP and scheduled appt Missing HbA1c; High HbA1c; High BP and appt next week 8/17-21) Missing HbA1c; High HbA1c; High BP and NO appt Missing HbA1c; High HbA1c; High BP and NO appt and Depression, Anxiety or ALZ Workflow % 38 Pre-Visit Prep 95 6% 5 Daily Huddle % 35 Schedule Appt % 11 Care Management and Schedule Appt Low-Moderate Risk (1840 Diabetics) # % Avg / PCP Workflow A1c 7-8, High BMI, Depression % 11 Coaching, BH A1c < % 45 Stay the Course!

28 Make HIT A Member of the Care Team EMR Registries Portals Mobile Devices Risk Stratification Care Gap Profiles Pre-Visit Prep Automated Outreach Quality Reporting Patient Service Rep or MA Schedule visits Activate standing orders Send out previsit communications Conduct follow up using automated Campaigns Care Manager Stratify patients by risk Reach out to patients with care gaps Coach through personal and automated patient education Physician Review Registries Assign high risk patients to Care Managers Address all diabetes care opportunities at every encounter CMO/Quality Committee Review performance by location and provider Meet with MDs and Care Teams at least monthly to review progress

29 An Outreach Strategy is a Must 29

30 Optimize the Encounter: Pre-Visit Preparation and Daily Huddles

31 AUTOMATION THAT MATTERS Personalized for every patient Catastrophic All >9 A1c and no office visit are sent a text message to call care manager Chronic All >9 and BMI >35 are sent an automated invitation to a group visit with diabetes dietician At risk All between A1c 7 and 9 are sent to an automated message to encourage visit website to take diabetes self-management course Healthy All diabetic <7.0 are sent an message emphasizing the importance of nutrition and exercise to maintain low A1c levels with a link to a mobile app to track their progress 31

32 The Patient s Agenda Steers the Interventions Our agenda for Oscar: Medication adherence Come to follow-up appointments Improved self-monitoring Participation in PT Nutritious food choices and increased calories Living Will Participate in Shared Decision- Making Oscar s agenda for Oscar: Grieving for his wife Transportation Managing Rx side effects Seeing his grandchildren

33 Avoidable Admissions: Engage Patients Sooner

34 Most Factors that Impact Health are Not Clinical Exogenous data (Behavioral, Socioeconomic Environmental) 60% of determinants of health Genomics data 30% of determinants of health Clinical data 10% of determinants of health Source: The Relative Contribution of Multiple Determinants to Health Outcomes, Laura McGovern et al., Health Affairs, Health Policy Brief,

35 Continuous QI Highest risk Collaborates with Planned Care Team Can be practicebased, shared or centralized Complex Care Team (5%) Quality Management (Across Practices) Planned Care Team (95% of patients) Tracks performance overall and by payer Initiates improvement projects with Care Teams Usual Care Between Visit and Chronic Condition Care HIT Platform Adapted from: Cambridge Health Alliance Model of Team-Based Care Implementation Guide and Toolkit

36 Moving To A Tech-Enabled 24/7 Patient-Centered Community Care Management Payer Patient Engagement Mobile Automated Outreach Patient Portals Patient Population of the Primary Care Office Clinical Analytics Clinical Decision Support Advanced Care Planning Claims and Cost Risk Stratification Primary Care Office Care of a patient Others who supply/require information and coordination Specialty Care Hospitals Referral Tracking/HIEs Device Radiology, Lab, Rx Distance Monitoring Telehealth/Telemedicine Remote Patient Monitoring

37 Smart Care Teams Current State Future State Care team Data & analytics Broad PCP-led team, with coordination across specialty and ancillary Integrated with hospital and specialty data using analytics based on clinical data and implied financial impact Patient-centered team fully integrated with specialty and ancillary that is multi-channel and 24/7 Integrated clinical, claims, financial, lifestyle, and biometric data providing real-time cognitive analytics Team activity Patient engagement pre/during/post visit using an approach based on patient segmentation Longitudinal engagement across care settings that is personalized and adaptive in real-time Workflow tools Clinical decision support tools within EMR and care management workflow solutions that leverage broad set of information Automated and actionable using full range of clinical, financial & lifestyle data, with a single integrated workflow across care team 37

38 Population Health: One Person at a Time Data and knowledge driven Every person has a plan Automation to manage a population down to the individual Team based 38

39 Questions? Thank You! Karen Handmaker

40 Wrap-Up Want to get involved? Speaker or topic ideas Key note presenter Blogger, twitter Contact Shelley Price Community Website

41 Next Steps JOIN US! Next meeting: Thursday, February 18, 2016 Architecting a Next Generation Data Platform: Quest Diagnostics Information and Analytics Blueprint Jason O Meara, MHA, BSE Director, Analytics Architecture Quest Diagnostics Healthcare Technology and Analytics Solutions

42 FY16 Leadership and Contact Information Co-Chairs: Mike Berger, PE Head of Population Health Analytics Mount Sinai Health Arthur Panov, MPH, CPHIMS HIT Architect IBM Watson Health HIMSS Community Organizers: Shelley Price, MS, FHIMSS Director, Payer and Life Sciences HIMSS

43 Thank You

44 Appendix

45 C&BI Committee Members John Middleton, MD, MSc FY16 C&BI Committee Chair VP/CMIO SCL Health David Butler, BSME, MBA, FHIMSS FY16 C&BI Committee Vice-Chair President Heartland Innovations, LLC Cheryl Bowman, CPHIMS* Data Manager University of Wisconsin Hospital and Clinics Raj Lakhanpal, MD, FACEP* CEO Spectramedix John S. Moses, MA Director of Enterprise Architecture, The University of Chicago Medicine Ravi Narayanan, MS Director, Research Data Management and Analytics Medica Research Institute Stuart Rabinowitz, MBA, BC* Director Federal Markets - Socrata Socrata Chester H Robson, DO, FAAFP* Medical Director, Clinical Programs and Quality Walgreen Co. Deborah Jane Rupe, RN, MS, FHIMSS Clinical Analyst, Shriners Hospitals for Children - Tampa Hospital Ahmad Sharif, MD, MPH, SCPM Chief Medical Information Officer, Resolute Health Louise Sulecki, MBA Systems Analyst, Cleveland Clinic * Indicates a returning committee member J.D. Whitlock, MPH, MBA, CPHIMS* Vice-President, Clinical & Business Intelligence Mercy Health

46 C&BI Community of Practice The goal of the C&BI Community is to bring together thought leadership and share knowledge that will support the future success of our members by improving their ability to understand and form partnerships to manage C&BI as a part of doing business and providing accountable and quality care to their members. The Community will support activities that promote peer-to-peer networking, problem solving, solution sharing, and education. Topics of focus may include: Storage and Management of Data and Supporting Technologies Knowledge Management to Support Accountable and Quality Care Case, Risk & Cost Management Best Practices Clinical & Business Analytics Clinical Decision Support Research Data Warehousing/EDW Data Lifecycle Management

47 C&BI Community of Practice Open to all HIMSS members (current membership: approx 6,700 people) Will meet virtually 6 times/year Agenda for the meetings may include: Commencing with a short series of 2-Minute Drills presented various Community members Topical discussion with key note presenter The 2-Minute Drill is based loosely on the sports analogy, and in this case is a fast-paced (short in length) presentation on a hot, emerging, or timely topic, news event (e.g. research paper, game-changing market or technology news), or recent and relevant event (e.g., federal public meeting, legislative/federal/judicial news, critical conference or educational event). 2-Minute Drills foster greater peer-to-peer networking, member engagement, problem solving, solution sharing, and education. If you are interested in presenting any drills, please contact Nancy or Shelley.

48 C&BI Task Force NEW! C&BI for Population Health Task Force CO-CHAIR: Karen Golden Russell, FHIMSS, MA, MBA Vice President, Population Health Verisk Health CO-CHAIR: Michelle Vislosky, M.B.A., FACHE Zone Sales Executive East Region of Canada & the United States Caradigm This group creates resources and tools that employ practical guidance and unbiased information to help healthcare organizations (providers, hospitals, integrated delivery networks, health plans and other stakeholders) use C&BI to harness, use and analyze data captured in the healthcare setting to execute population health management initiatives and improve care and health outcomes. Meeting times: 3 rd Tuesday of the month, 3:30-4:30pm ET