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Quality Health Care: Technology and Data Drive Improvement by Stephen Lieber

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Quality Health Care: Technology and Data Drive Improvement by Stephen, Lieber President and CEO, HIMSS Global, USA

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Quality Health Care: Technology and Data Drive Improvement by Stephen Lieber

  1. 1. 1 Quality Health Care: Technology And Data Drive Improvements H. Stephen Lieber President & CEO HIMSS
  2. 2. HIMSS Introduction • Who is HIMSS – Global-focused, not for profit organisation of professionals, clinicians, companies, policy makers and other stakeholders sharing the vision of better health through IT • How do we work – As a dominant voice, convener and thought leader of health transformation through IT • Who is HIMSS – 300.000+ engaged professionals, 65.000+ members, ~400 staff in Europe, Asia, Middle East and North America 2
  3. 3. We work with: • Governments and Ministries • Policy makers and strategists • Care providers • Suppliers and Vendors • Professional communities • Clinical experts & IT professionals 3
  4. 4. What drives our mission • Hundreds of thousands die in hospitals each year as the result of medical errors – Tens of thousands die from medication errors alone • Hundreds of thousands die each year without access to appropriate health care • In the EU, missed healthcare opportunities have a €70 billion cost to European society • These measures can be improved and IT is a major driver for that improvement 4
  5. 5. Common Issues for Global Health • Reducing hospital admissions, mortality • Reducing hospital acquired infections • Reducing “never” events • Reducing length of stay • Ageing population with multiple complications • Expanding community based care delivery • Improving patient safety • Improving efficiency and productivity • Justifying the investment in technology5
  6. 6. 6 High Correlation: Advanced EMR Capabilities and Quality
  7. 7. EMRAM: Model to Drive IT-Influenced Better Care • Research shows relationship between higher levels of IT adoption and patient outcomes, safety • EMRAM established globally-recognised pathway for IT adoption • Baseline study will identify gaps, inform strategy development • Standardised measuring tool of improvement 7
  8. 8. 8
  9. 9. • Apollo Hospitals Aynambakkam • Apollo Hospitals Chennai • Apollo Health City, Jubilee Hills • Apollo Speciality Hospital, Nandanam India • Max Super Speciality Hospital, East Wing, Saket • Max Super Speciality Hospital, West Wing, Saket
  10. 10. Hospital Mortality QUESTION: What is the association between EMR capabilities and hospital mortality? • Paired HIMSS Analytics EMR Adoption Model (EMRAM) scores with Healthgrades’ hospital quality/mortality data. In General… the more advanced the hospital’s EMR capabilities… the more likely the hospital is to have better risk-adjusted mortality rates when treating conditions like Heart Attack, Heart Failure, Stroke, several types of GI surgeries, Pneumonia, Sepsis and Respiratory failure. 10
  11. 11. US Hospitals with an "A" Leapfrog Hospital Safety Grade by EMRAM Stage 0.0% 5.9% 12.8% 14.3% 20.1% 21.8% 30.8% 62.6% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0% Stage 0 Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 Stage 6 Stage 7 AllhospitalswithineachEMRAMStage Tipping Point
  12. 12. 1.62% 2.84% 2.25% 2.35% 3.53% 4.06% 3.91% -1.52% -0.58% 0.77% 1.79% 1.47% 2.55% 2.20% 4.91% -2.00% -1.00% 0.00% 1.00% 2.00% 3.00% 4.00% 5.00% 6.00% 0 (2008 N = 392; 2011 N=225) 1 (2008 N = 354; 2011 N=171) 2 (2008 N = 850; 2011 N=400) 3 (2008 N = 1060; 2011 N=1303) 4 (2008 N = 88; 2011 N=369) 5 (2008 N = 55; 2011 N=202) 6 (2008 N = 48; 2011 N=144) 7 (2008 N = 0; 2011 N=13) MeanOperatingMargin EMRAM Stage In 2008 In 2011 … HIT can achieve ROI ! Operating Margin by EMRAM Stage Quelle: HIMSS Analytics US Database
  13. 13. Who’s Using This  Denmark – annual data collection from all Danish hospitals to monitor status quo & provide input to new national ehealth strategy to achieve nationwide fully integrated care  Finland – with the HIMSS continuity of care model, HIMSS will support Finland in their new organizational transition, providing a strategy for regional integrated care  UK – data collection from all hospitals; gap analysis & assessment  Spain – annual data collection from 6 Spanish regions, gap analysis and investment strategy recommendations; CPHIMS education/certification for healthcare professionals  Turkey – annual data collection of 850 public hospitals to monitor investments, provide gap analysis & investment recommendations. New! Standards development & training/certification of Healthcare professionals  Iceland – data collection, gap analysis, investment recommendation  European Commission: co-organize largest annual European joint HIT event eHealth week presenting future roadmap for eHealth in Europe13
  14. 14. 14 IT Drives Care Delivery Transformation
  15. 15. IT Allows Focus on Patient Not Episode • Better care outcomes at lower consumption of resources • Break down silos across care providers to achieve: – A dynamic interconnected community wide focus: • Health Information Exchange • Coordinated patient care • Patient engagement • Advanced analytics •HIMSS has developed global model to provide comparative framework, gap analysis, and directional guidance 15
  16. 16. Continuity of Care Maturity Copyright © HIMSS Analytics
  17. 17. Continuity of Care Maturation Model Model Overview • Improve care coordination over diverse care settings • Engages 3 key stakeholder groups • Leverages an 7 stage maturity model, like EMR Adoption • 4 key focus areas theme for each stage, across entire model • Aspirational model drives value based care approach • Simple assessment survey • Action oriented, strategically focused deliverables
  18. 18. 18 Data and Analytics: Going Beyond IT Systems
  19. 19. Analytics Value Curve Descriptive Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics Hindsight Insight Foresight What happened? Why did it happen? What will happen? Can we make things happen? Less Difficult More Difficult
  20. 20. Why a maturity model • Learn from others experiences • Provides a roadmap • Helps convey a vision of target state • Encourages everyone to work collectively 20
  21. 21. Key Focus Areas Across All Stages • Data Content growth – Basic data to advanced data – Aligned with clinical, financial, and operational analytics activities • Analytics competency growth – Start simple and work to master specific competencies – Enhance performance tracking / clinical decision support – Appropriate analytics maturation for individual parts of the organization • Infrastructure growth – Flexible approaches to accommodate a wide variety of situations – Vendor neutral – Timely data, centrally accessible • Data Governance growth – Quality data and resource management – Executive suite and strategic alignment
  22. 22. Building Blocks to Quality • Sophisticated IT Adoption • Continuity of Care • Data and Analytics 23
  23. 23. 24 Thank you H. Stephen Lieber slieber@himss.org www.himss.org

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