Mobile Health at Ochsner: The Apple HealthKit and Epic EMR Integration
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"Empowering Consumer with Smart Devices and Smart Data for Proactive ‘Health Care’" - Maryam Ziaei (Founder/CEO, iSono Health)
- 1. Democratizing Healthcare
- 2. Patient- Centered Healthcar e HOSPITA L HOME Personalized What’s the best care for my needs? Predictive What health trends that are likely to develop? Proactive Who’s at risk? Who needs to be informed? Preventative What actions can I take now to prevent disease?
- 3. Proactive Personalized Health: Move to LEFT Health Status 80% of Cost from 20% of Population
- 4. Personalized Medical Home Smart Sensing Intelligent Information Management Effective Interfaces Putting the patient at the center of their health system Family & Friends Healthcare Providers Web Repositories Healthcare Institutions Researchers
- 5. Smart Devices Connected Systems End-to-End Analytics Patient-Centric Home Health Smart Big Data Actionable Insights
- 6. Smart Devices Connected Systems End-to-End Analytics Smart Sensors for Every Sense
- 7. Smart Devices • Non-invasive wearable sensors • Personal biosensors • Environmental sensors • New data streams + machine learning = “New vital signs”
- 8. Smart DevicesSmart Devices
- 9. Smart DevicesSmart Devices
- 10. Smart Devices
- 11. Smart Devices
- 12. Consumer Technologies Social Media Technologies Internet Technologies Visualisation Technologies Learning Technologies Enabling Technologies From glasses to wearables VLE PLE Collective intelligence Collaborative environments Next gen batteries Wireless power Tablet Quantified self 3D printing Information Visualisation Drivers of Disruption in Healthcare
- 13. Smart Phone
- 14. 3D Printing
- 15. Machine Learning Tags Abnormalities Human-Centered Design Adoption + Adherence Human Nature Admires Complexity but Rewards Simplicity.
- 16. Effective Interfaces • Multimodal – GUI, touch, gesture, speech, … • Mobile – Portable, networked, wearable • Intuitive – Easy to learn, use, maintain • Adaptive • Proactive
- 17. Machine Learning Tags Abnormalities Security Privacy Compliance
- 18. Machine Learning Tags Abnormalities > 400 Million Units by 2020
- 19. Machine Learning Tags Abnormalities Patient Generated Data Big Data
- 20. Intelligent Information Management • Longitudinal data – Personal baseline – Detect trends & deviations from norm • Personal health records – Privacy – Sharing – Anonymous aggregation • Patient-centered decision support
- 21. Data Aggregation and Analytics
- 22. Artificial Intelligence for Predictive Healthcare
- 23. From Data to Decisions
- 24. REACTIVE PROACTIVE SPORADIC CONTINOUS
- 25. Machine Learning Tags Abnormalities EARLY ENAGEMENT = SUCCESS in Healthcare
- 26. 28
- 27. Regular Accessible Breast Health Monitoring
- 28. 1 in 8 women WILL BE DIAGNOSED WITH BREAST CANCER
- 29. Machine Learning Tags Abnormalities EARLY DETECTION = 99% SURVIVAL
- 30. 1 in 3 BREAST CANCERS IS MISSED
- 31. 47% of women have dense breasts BUT Mammogram misses tumors in dense breasts Breast Cancer screening is sporadic, inaccessible, and expensive High risk women need more regular screening
- 32. Current Breast Ultrasound Sources: American Cancer Society, American College of Radiology Image Quality is Operator Dependent False Positive
- 33. Cost ~ 5-10K SonoSite PhilipsGE VSCAN GE Siemens Cost ~ $200-400K 35.7% More Cancer Detected with Automated Breast Ultrasound * Point-of-Care Automated
- 34. 3D ULTRASOUNDWEARABLE MOBILE APP Automated + Low-Cost 2 Patents
- 35. Machine Learning Tags Abnormalities
- 36. Machine Learning Detect Changes EARLY and Track Over Time
- 37. 2 Minutes Scan No Radiation Actionable Feedback
- 38. Clinical Study with 100 Women iSono GE
- 39. Early Adopters Market of $4B CAGR of 10.8% Pricing: $300/Device $20/User/M onth ARR US Market 8.6M Women at Very High Risk Total Addressable Market of $32B 102M Women over 30 in US
- 40. Early Stage Diagnosis $20K pp Late Stage Diagnosis $100-300K pp $18.5B Direct Cost of Breast Cancer + $14B Lost Productivity Per Year for self-insured employers and health insurance companies Why Would Payers Care?
- 41. 44 Regular and Accessible Breast Health Monitoring $32B Market
- 42. Personalized, Proactive Healthcare Better Health Better Care Better Value maryam@isonohealth.com
- 43. Making Sense of Big Data • Understanding human behavior from sensor data – Integrating vastly different kinds of data – Incorporating commonsense knowledge – Compute intensive methods for learning & inference • Embedded, mobile, and distributed systems – Data transport in dynamic, heterogeneous environments – Security and data sharing – Data / annotation / interpretation streams
- 44. 49 System Concept Personal Health Monitoring • Preventative Healthcare • Chronic Care Management • Post-surgery Monitoring • Borrow from the field of machine health monitoring – Identify the most minimally invasive ways to capture data – Mine collected data to identify personal baselines, data defined models and track changes – Identify patient preferences and create a system that gives a valuable user experience – Identify effective ways to share data with health care providers Measure • Cardiac function (ECG) • Respiration (Sound/ECG) • Activity (Accelerometry) Alivetec ECG & motionTouch screen mobile phone
- 45. Personal Health Management Assistant • Provide effective, intuitive access to information in Personal Health Record • True conversational interaction – UR Computer Science leading center of research on dialog systems – Not just canned responses: reasons about user model and dialog context • Target population: Heart failure patients following self-care guidelines – Collect information relevant to condition – Interpret with respect to self-care guidelines – Suggest appropriate course of action – Facilitate information sharing with doctors & family
- 46. Smart Sensors
- 47. Go-to-Market Strategy High Risk Women Surveillance Women over 30 Screening Channels & Partners • Women Healthcare Centers • BC Advocacy Groups • Genetic Testing/Counseling • Corporate Wellness • Mail-in-Subscription • Walk-in Health Clinics Breast Cancer Patient Monitoring • Breast Cancer Centers • BC Pharma
- 48. 1Billion Women need additional screening 50M Women at Very High Risk due to Family History or Genetics Every Year 1.7M New Cases of Breast Cancer Market Over 500,000 Breast Cancer Deaths/year
- 49. Competitive Landscape Portable Ultrasound Automated Ultrasound 35% More Cancers Detected Cost: $200K + Wearable Sensor Solutions Cost: $5-10K Disadvantage: Probe Operator Error
- 50. 1Billion Women over 30 in the World with Dense Breasts 50M Women at Very High Risk due to Family History or Genetics Every Year 1.7M New Cases of Breast Cancer Market Over 500,000 Breast Cancer Deaths/year
- 51. Early Adopters Market of $4B CAGR of 10.8% Pricing: $300/Device $20/User/M onth ARR US Market 8.6M Women at Very High Risk Total Addressable Market of $32B 102M Women over 30 in US
- 52. European Market Every Year 500,000 New Cases of Breast Cancer Over 140,000 Breast Cancer Deaths/year 14M Women at Very High Risk due to Family History or Genetics Early Adopters Market of $8B
- 53. Women with Dense Breasts Sporadic and Inaccessible Screening High Risk Women
- 54. Current Breast Cancer Screening Self Breast Exam Ineffective for small tumors Mammogram Low Sensitivity X-ray Radiation
- 55. 1Billion Women over 30 in the World with Dense Breasts 50M Women at Very High Risk due to Family History or Genetics Every Year 1.7M New Cases of Breast Cancer Global Market Over 500,000 Breast Cancer Deaths/year
- 56. Quantitative Ultrasound + Machine Learning • A multi-parameter longitudinal approach improves precision Grayscale Image Qualitative features • Shape • Contour • Shadow Raw RF signal Quantitative features • Power spectrum • Statistics • Frequency dependence Parametric Change Longitudinal features • Volume density • Cell death/growth • Tissue acoustic properties
- 57. FDA Regulatory Roadmap Research and Development Pre-Clinical Development Clinical Testing FDA 510(k) Approval Concept Design Control Design Iterations Repeatability Testing Submit 510(k) Package FDA Review & QuestionsPackaging & Labeling Biocompatability Repeatability Testing Electrical & Mechanical Testing Repeatability Testing IRB/IDE Approval Neo-adjuvant Chemo Trial 12weeks ~100 Patients Human Factor Study ~50-75 Users Efficacy Best Case Scenario: Class II 510(k) no clinical study • Predicate found already • Expected clearance 5-6mo • Need 50 users for usability Validation Development Worst Case Scenario: Class II 510(k) DeNovo - Expected clearance 10- 12mo - Need 100+ users for clinical Efficacy We’re Here
- 58. Screening Today Self Breast Exam Mammogram Insurance Covers >50 Ultrasound $500 MRI $ 2000
- 59. Go-to-market Timeline ✔ Q3 2015 ✔ ✔ Q1 Q2 Q3 Q4Q4 2016 ✔✔ 2017 ✔ Q1 Q2 2018
- 60. Partnerships iSono Health’s compact, low-cost, automated ultrasound system enables Remote Patient Monitoring for: Neoadjuvent Chemo Patients, BC Clinical Trials Tracking Response to Treatment Personalized Treatment Early Stage BC Patient Post-Lumpectomy Recurrence Monitoring Breast Conserving Surgeries High Risk Women with Family History, Genetics Surveillance Early Stage Detection Healthy Women with Dense Breasts Supplemental Screening False- Negative/Positive Reduction
- 61. Customer Validation In a national survey of 1000 women, 38% have responded favorably to purchasing our device "Amazing idea. Anything that can give anyone a more sound piece of mind or the ability to see something sooner is a great tool." "Please keep me informed of the details of this product." "I'm very excited about this being a viable option for preventative screening!" "I would be excited to have access to a device like this. I live in a rural area with little access to Healthcare. I have been diagnosed with BRCA1 mutated gene … this would help me be proactive." 68% of high-risk women self- reported as “very/extremely willing” to purchase our device
- 62. Device Machine LearningCloud iSono IP Strategy - Array Architecture Transducer Assembly - 3D Image Processing -Tag and Measure Breast Masses -Track changes over time - User Interface - Scan Analytics - Genetic + Scan Actionable
- 63. Cost ~ 5-10K Current Ultrasound Trends: Cheaper, Automated SonoSite PhilipsGE VSCAN MobiSante Image Quality is Operator DependentGE Invenia (Acquired U Systems) Siemens ACUSON S2000 SonoCine Cost ~ $200-400K 35.7% More Cancer Detected with Automated Breast Ultrasound* Compact Ultrasound Probe Systems Sources: MarketsandMarkets, Frost and Sullivan *http://www.fdanews.com/articles/164936-ge-healthcare-nabs-fda-approval-of-invenia-abus-breast-imaging-technology
- 64. How Does it Work? Comfortably wear the bra accessory. Attach scanner to ring on either breast. Open iSono app press “scan.” The scan completes in 1 minute. Attach device to the second ring on the other breast. Our software will process images and tag any changes. Physician receives your tagged images & sends you feedback via the app. The app will remind you of the next scan in 1 month.
- 65. Real Time Data Real Time Feedback Faster Return to Work Less time in hospital/healthcare facilities reduced cost Post surgery monitoring
