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Harnessing Population Health Management to Promote Quality Improvement in Healthcare by Judy Murphy

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IBM Global Healthcare & Life Sciences

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Harnessing Population Health Management to Promote Quality Improvement in Healthcare by Judy Murphy

  1. 1. Harnessing Population Health Management to Promote Quality Improvement in Healthcare Judy Murphy, RN, FACMI, FHIMSS, FAAN Chief Nursing Officer IBM Global Healthcare & Life Sciences
  2. 2. Slide 2 What we will cover: – Evolving healthcare landscape – what is changing and why we need to change too – Population Health Management – Reimagining Health and Healthcare with Mobile – Population Health Management requires Patient Engagement – Emerging Consumerism and eCommerce – The Need for Analytics – The Era of Cognitive Computing (Watson)
  3. 3. Healthcare transformation is happening, driven by fundamental shifts in expectations and critical drivers Expectations for better quality, value and outcomes Escalating incidence and cost of chronic disease Changing demographics and lifestyles Globalization of health care Critical resource shortages Increased competition and new entrants Advances in technologies and treatments Slide 3
  4. 4. Old Healthcare New Healthcare Fee for service Pay for performance Volume Value Delivery Quality Outcome Employer-centric Consumer-centric Prices unknown Cost transparency One way dialogue Engaged & mobile Transactional Brand loyal Data poor & disconnected Integrated rich “big” data Reactive Predictive & prescriptive Standards Personalized & optimized This transformation is an evolution … to a new model for healthcare Slide 4
  5. 5. Healthcare is moving to a system focused on value, coordinated around the individual, and integrated into our communities Focus is on value, coordinated around the individual and integrated into communities Emphasis is on proactive care to meet health needs Payment will be based on value and outcomes Care is standardized according to evidence- based guidelines We measure quality and make rapid changes to improve it Data and Information Understand and influence their populations Evidence-based and standardizedcare planning Coordination across boundaries -- share care, accountability and risk Individual engagement and empower- ment Quality measurement and performance reporting Social Worker Behavioural Health Family Community Pallative Care/ Hospice Rehabilitation Home Care Specialists Intensivist Physical Therapist Dietician Case Manager Caregivers Transportation Housing Medications Funding and Payment Primary Care Slide 5
  6. 6. The new model is Value Based Care – centered around the patient Value = Experience Cost Taking steps to achieve better results, and improve customer (patient) satisfaction Reducing waste, reducing errors, managing risk, improving efficiency and quality Organizations are on a journey to improve value Slide 6
  7. 7. Population Health Management HEALTHY / LOW RISK CHRONICAT RISK ACTIVE DISEASE No or very-low touch Medium to high touch Low touch High touch 40-60% 5-15%20-25% 2-3% 60+ 5-10% 30-40%15-20% 40-50% RISK STRATIFICA TION POPULATION RELATIVE COST ENGAGE MENT Fully automated Validate from data Blended - retail outlet, care mgt, automated Mostly automated with email, call, text, mobile app Active Case Mgmt OUTREACH Capability Needs • Data (internal-external) • Scalable platform/data management • Risk analytics & management • Insight analytics • Similarity analytics • Cost of care analytics • Actuarial analytics • Marketing analytics • Marketing management • Predictive modeling / next best action • CRM • Campaign management • Outreach advisor • Remote data capture • Mobile apps • Network analytics • Care coordination tool/ clinical integration~20% of population drives ~80% of cost ENTIRE POPULATION Slide 7
  8. 8. Reimagining Health & Healthcare with Mobile Slide 8
  9. 9. Mobile is being exploited to: Facilitate anytime anywhere access to data and extend services beyond traditional settings Develop new engagement techniques and health strategies with patients and consumers Gain insights to provide more personalized, proactive interventions; bring analytics to the point of care Slide 9
  10. 10. Imagining Care Anywhere Slide 10
  11. 11. The Power of Patient Engagement: Population Health Management requires Patient Engagement Capture and incorporate preferences Personalize offerings and services Innovate to deliver quality, convenience and total experience “Know me” “Engage me” “Empower me” • What’s my history? • What are my preferences? • How will I respond? • What will motivate me? • Respect my privacy • Engage in the preferred dialog • Be relevant (“right information”) • Be consistent across touch points • Show sincerity -- “you care” • Give me the information I need • Connect me with relevant communities • Simplify control and access • Enable action and convenience Slide 11
  12. 12. Trends Supporting Greater Patient Engagement The way we pay for and deliver care is changing. Health IT adoption has reached a tipping point. Technology is getting better, cheaper, faster and more ubiquitous. Consumers increasingly expect online engagement, in all aspects of their lives. Slide 12
  13. 13. Integration of health in our lives Slide 13
  14. 14. So what is driving “Consumerism” in healthcare? Source: Healthcare Payer News, May 2014 • Cost shifting – “out of pocket” costs are increasing for individual healthcare consumers • There is an increase in the use of High Deductible plans and Health Savings Accounts (HSAs), leading to more consumer price sensitivity Slide 14
  15. 15. New business models for delivering care are emerging, providing people with more “choice” Slide 15
  16. 16. Health Plan Engagement App Demo Consumer “Shop & Buy” activities Slide 16
  17. 17. Successful healthcare organizations thrive by using analytics as a core strategic foundation Early and accurate insights on member health risk and utilization to inform Financial / Actuarial decisions Patient-360 insights to inform Medical Management in chronic disease & episode management Insights into referral patterns and provider quality to support Network Design and Management Inform program design & operations for Marketing & Sales and Customer Service with insights on consumer preferences & triggers Population Health Risk Management Consumer Engagement Provider Relations Support Business Functions Impact Continuumof Care Sample Analytics Applications Facilitate insights exchange & messaging across care team members. Inform incentives design. Enabling analytics to empower ACOs and providers to succeed in value- based payment transformation Next best action analytics leveraging real-time data to optimize omni- channel consumer engagement Provide tools to providers to enhance risk stratification and clinical decision making Care Path Mining Network Optimization Personality Insights Consumer Segmentation Risk Stratification Utilization Prediction Cost Patten Detection Channel Optimization Resource Allocation 17 Slide 17
  18. 18.  What is the optimal treatment based on the latest literature for my patient’s clinical profile?  Why is this the best protocol? Basic Reporting  What happened?  When and where?  How much? Foundational Analytics  Who is at risk?  What is happening?  How can we improve?  What is the Right Data?  What actions to take? Enterprise – Wide Data InsightsRetrospectiv e Reporting Proactive Interventions and Improved Outcomes  Data Governance  Centralize Data  Structured and Unstructured  Data Sharing  Cost of Care Intelligence  High latency reporting  Spreadsheets  Limited view reports  Dept data marts  Population Health Analytics  Evidence-based medicine  Streaming Analytics  Similarity Analytics Natural language understanding Guided consumer experience Watson Applications Clinical Content Analysis Personalized Healthcare Dynamic Learning for Optimal Care Guidance Predictive & Prescriptive  What will happen?  How can we pre-empt?  What is the likely outcome? Who would be best at managing this patient?  What is the expected response to potential medications? CognitiveThe Healthcare Analytics Journey 18 Slide 18
  19. 19. Published Knowledge WATSON Patient Care and Insights Knowledge-Driven Methods Data-Driven Methods Observational Data Longitudinal health records Claims data Patient reported data Scientific papers Books Guidelines Patient Similarity Analytics Identification of evidence- based best practice From population averages … To insights for individual patients Analytics strategy must span both knowledge & data-driven methods 19 Slide 19
  20. 20. Trusted Information Platform Predictive Dashboards Natural Language Cognitive Computing ‘Big Data’ Volume, Velocity, Variety… Patient Similarity Healthcare Analytics Progression Slide 20
  21. 21. Watson is ushering in a new era of computing 1900 1950 2011 Slide 21
  22. 22. Cognitive Systems Era Discover and Decide Interact Naturally Learn and Reason Slide 22
  23. 23. Watson May Help Beat Cancer Slide 23
  24. 24. Slide 24 Thanks! Judy Murphy @JudyMurphyHIT