Big Data Analytics Driving Healthcare Transformation

Transcription

1 Big Data Analytics Driving Healthcare Transformation Greg Caressi SVP Healthcare & Life Sciences November, 2014

2 Six Big Themes for the New Healthcare Economy Themes Modernizing Care Delivery Clinical practice is moving from intuition based decisions to more analytics and data based approaches. Role of New Participants The emergence of IT based tools and services is witnessing the rise of a new breed of competitors. Rethinking the Customer Patients are no longer going to be passive participants in the process. Who Pays? -The spiraling costs of care to government and private payors is forcing the launch of new methods and models for payment of healthcare services and products. Companies Revamping Strategies Many industry participants as currently structured can not maintain viability without significant changes to their business model. New Partnerships An industry that historically operated in distinct silos is now being forced to integrate, and thus leading to firms seeking new types of partnerships and collaborations. Source: Frost & Sullivan analysis. 2 2

3 Size of Impacted Population Care Delivery Transformation: Acute Care to Prevention Track, Predict, Intervene, Manage Goal: Keep People Healthy Longer Prevention/Wellness Goal: Manage or Mitigate Risk $$ Goal: Diagnose and Reduce Treatment Delay Early identification and prevention New models of care delivery to improve: Collaboration among providers Patient knowledge, self-help and health Increase intervention Higher touch at lower cost Goal: Move to More Interaction and Self- Mgmt Disease/Care Management Goal: Manage Goal: Quality of Life Healthy / Well At Risk Undiagnosed Chronically Ill Managed Chronically Ill Unmanaged End of Intervention Continuum of Care Source: Frost & Sullivan 3

4 Data Creating Value in Healthcare Improved patient safety Tracking of key metrics Collaboration Flexible access Real-time info Rapid intervention Early trend identification Reduce response time Combine info for insights Auditable Improved visualization Innovation Efficient stakeholder interaction Reduce capital, staff costs 4

5 Leveraging Big Data to Reduce Healthcare Costs Imaging files Published research EHR / EMR Social media Remote monitoring mhealth apps Genomic data , text messages Clinician notes Microbiomic data Metabolomic data Natural Language Processing Analytics Cues to intervene Patient engagement Claims data Biometric sensors Photos, video 5

6 More Traditional Healthcare Analytics New Analytics Tools Needed By ACOs Types of Analytics Applied in Healthcare Big Data Solutions COMPARATIVE ANALYTICS PRESCRIPTIVE ANALYTICS DESCRIPTIVE ANALYTICS PREDICTIVE ANALYTICS What Happened? What Will Happen? Source: Frost & Sullivan 6

7 Who s At-Risk? Many Layers of Analytics In Preventive Care Reduce utilization by frequent flyers Avoid readmission penalties Avoid catastrophic events in diagnosed patients Better disease management to reduce long term costs Reduce the number who develop chronic conditions 7

8 Hurdles to Reaching the Promise of Digital Health DATA INTEGRATION ANALYTICS SUSTAINABLE CHANGE We are creating millions of useful data points, from a wide variety of sources But the data is provided in separate solutions which prevent getting a holistic view of the patient. FREEING DATA AND INTEGRATING DATA ARE KEY Predictive analytics has arrived Prescriptive insights from omics are next Interpretation needed to make genomic data valuable Analytics alone cannot transform healthcare. What actions are taken based on analytics? - Behavior change - Process change - Organizational culture change Source: Frost & Sullivan 8

9 IT Transformation Helping To Drive Healthcare Transformation Cloud Measure Outcomes Define Population AUTOMATED & ONGOING Social Media Cloud Mobility Manage Care Data Integration Analysis Reporting Communications and Alerts Identify Care Gaps & Stratify Risks Big Data Cloud Big Data Engage Patients Social Media Mobility Cloud Source: The Institute for Health Technology Transformation, 2013; and Frost & Sullivan 9

10 Cloud Solutions Are Aligned With Healthcare Shifts Cloud allows scale in storing big data Collaboration requires flexible access and merged data sets Collaboration in research means moving partners to the data Cloud frees data from proprietary enterprise software solutions Cloud solutions reduce impact of IT staff shortages Cloud is a key enabler of mobilizing data for use by consumers and enterprise users Source: Frost & Sullivan analysis 10

11 Business Model Transformation 11

12 What Will Healthcare Organizations Invest In To Address Changing Goals? Inpatient Care Ambulatory Care Home Care Wellness Services CDS at point of care Data Analytics Imaging Diagnostics Patient Engagement Chronic Disease Mgmt mhealth Conditions of focus Diabetes Cardiovascular conditions, e.g., Congestive Heart Failure, Chronic Heart Disease Hypertension Chronic Obstructive Pulmonary Disease (COPD) Source: Frost & Sullivan 12

13 Competitive Success Factors Change Who Will Win Last Decade Current Decade Next Decade Success Drivers Technologies geared towards extending life Technology to improve outcomes and mitigate risk Integrated platforms to provide comprehensive continuum of care. Focus on quality of life. Types of Companies Who Excel Companies that advanced standard of care. Companies that could make treatments safer and easier to perform. Companies that understand consumer behavior, needs, and pain points. 13

14 Business Models Must Adapt Yesterday Product focus only (vs solution, service, software, support) All innovation is technologybased (vs process, efficiency) Individual clinician as customer Tomorrow? Frugal innovation, tiered product markets Start with the need, not with the technology Look beyond your core customer base Know when to fold Creates new data stream in isolated silo Applying techniques from other industries to healthcare 14 14

15 New Ecosystems In Development S Health Platform Value added through Data integration platform New apps, analytics built on integrated data Holistic view of individual health and fitness Business model = drive smartphone / tablet sales or health / wellness services? 15

16 Moving to the Consumer 16

17 Direct To Consumer Models Regulatory issues to address Will consumers make treatment decisions based on the information provided? Is a clinician interface needed to present information to the consumer? Genetic profile only versus risk analysis Research to support interpretation of risk assessment Next step toward addressing consumer questions opportunity or risk? Content or services needed beyond the data? Moving from Dr Google to Dr Watson as a consumer resource How is the solution delivered to the consumer? Clinician or service interface to assist with next steps and interpretation? 17

18 Leveraging mhealth to Reduce Avoidable Medical Costs Key Pain Points Addressed by Current mhealth Technologies Patients don t follow their prescriptions Patients don t give doctors enough information Unnecessary visits to doctors Missing critical warning signals Unhealthy diet & lack of exercise Annual Cost to US Healthcare System ~ $300 billion ~ $45 billion ~ $125 billion ~ $7 billion ~ $100 billion mhealth Technology Help patients track the timing & dosage of their medicines Help providers gain more insight into patients conditions & behavior to offer the right treatment & advice Provide information on side effects, benefits, etc. Collect data through an application which keeps consumers engaged with the help of games, content and interaction Flag potential health problems and figure out exactly which people on the medical team they need to see Provide information to patients by allowing them to pose health related questions to a network of physicians Video teleconsultations Allow doctors to remotely monitor the vital signs of hospital patients and at home through sensors/devices Allow people to track calories through weight-control applications Prompt people to set reasonable goals, exercise, and count calories Source: mhealth report published by PwC, 18

19 Mobile Platforms Offer Many Ways To Interact With Patients Medical mobile apps enable patients to continuously monitor their health and share data with providers, thus encouraging an ongoing focus on wellness that extends beyond the office and live visits to the doctor. Diagnostic Tools EHRs/PHRs Data Exchange/ Secure Messaging Decision Support You can take the phone and make it a lab on a chip. You can do blood tests, saliva tests, urine tests all kinds of things sweat tests, through your phone. This is a powerful device. * Educational Content Biometric Monitoring Social Networks Lab & Imaging Results *Eric J. Topol, M.D., West Endowed Chair of Innovative Medicine at Scripps Health and Professor of Genomics at the Scripps Research Institute and author of The Creative Destruction of Medicine: How The Digital Revolution Will Create Better Health Care (Basic Books, 2012) Source: Frost & Sullivan 19

20 Market Size (billion $) Wearable Technology Driving Current mhealth Market Market Potential and Growth Projection (Global, ) Sensor technology will continue to advance and create better biometric data Winners based on brand vs sensor capabilities vs style, fashion? Will all devices be commoditized over time? Nike decision to exit devices Fitbit decision to not integrate with HealthKit 20

21 Thank You Greg Caressi Senior Vice President Healthcare & Life Sciences (+1)