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POCD in Public Health Scenario: A peep into the future by Michael Greenberg


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POCD in Public Health Scenario: A peep into the future by Michael Greenberg, CEO-Fio Corporation,

Published in: Healthcare
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POCD in Public Health Scenario: A peep into the future by Michael Greenberg

  2. 2. 2 Confidential What quality of healthcare is mostly delivered? How well is money mostly spent? No one actually knows! 95% health care data is from centralized facilities 95% patient encounters are in decentralized facilities Billions patients/yr $8 Tr/yr, globally $2 Tr/yr, LMIC $30 B/yr, aid
  3. 3. 3 Confidential Big Disconnects in Decentralized Healthcare Data: little to no point-of-care data for remote managers and stakeholders Care: non-standardized, under-supervised care by frontline health workers Health workers don’t capture data because it competes with delivering care
  4. 4. 4 Confidential Insight PortalMobile Intelligent Devices Cloud Services Health workers of all levels:  deliver care on par with experts  do diagnostic tests on par with experts Stakeholders of any kind:  get tracking, analytics, insight  real time, anytime, anywhere : Integrated Care & Insight System Connectivity Broker
  5. 5. 5 Confidential Mobile Point-of-Care Full Companion Automated Workflow Guidance │ Universal Rapid Test Reading │ Connectivity │ Data Capture
  6. 6. 6 Confidential Enables Connectivity for 3rd-Party Devices 3rd-Party Devices 300+ 3rd-party peripherals, devices, sensors: weight, blood pressure, heart rate, ECG, lipid profile, pulse oximetry, blood glucose, haemoglobin, CD4, spirometry, fetal monitoring, digital thermometer, … Health Workers at Point of Care Cloud Services Key Stakeholders of Any Kind 3rd-Party Health Information Systems
  7. 7. 7 Confidential Capture last- mile data from care processes Extract multi-level insights Inject insights into care processes Care Drives Insights, Insights Drive Care
  8. 8. 8 Confidential Fig 1: Documented rapid diagnostic test (RDT) performance Fig 2: Automatically reduced RDT error rate 10-fold Fig 3: Fionet profiled health worker performance 0% 50% 100% Health Worker 14 Health Worker 13 Health Worker 12 Health Worker 11 Health Worker 10 Health Worker 9 Health Worker 8 Health Worker 7 Health Worker 6 Health Worker 5 Health Worker 4 Health Worker 3 Health Worker 2 Health Worker 1 Valid Result Obtained Human Error in RDT Processing RDT overloaded with blood Blood erroneously in buffer well 0% 5% 10% 15% 20% 25% 30% Week 1 Week 3 Week 5 Week 7 Week 9 Week 11 Week 13 Error Rate ErrorRate Transformed Point-of-Care Diagnosis
  9. 9. 9 Confidential Fig 1: Compliant vs non-compliant treatment for confirmed POSITIVE diagnosis 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% Each column: an individual clinic’s treatment records of all its patient Percentage of cases in which clinic complies with healthcare provider’s treatment protocol Fig 2: Compliant vs non-compliant treatment for confirmed NEGATIVE diagnosis Transformed POC Treatment Percentage of cases in which patients do not get the drug they need Percentage of cases in which patients get a drug when they don’t need any drug
  10. 10. 10 Confidential Fig 2: health worker utilization shown in real timeFig 1: consumable shortages shown in real time at capacity overloaded under-utilized health workers Transformed POC Business Process Metrics
  11. 11. 11 Confidential Fig 3 Tracks drugs prescribed across clinics Fig 1 Tracks error rates of rapid tests, by manufacturer ErrorRatebyRDT Manufacturer Sample Size Mfg Error Rate Mfg B 8,450 0.12% Mfg S 13,259 1.61% Mfg A 12,565 3.94% Transformed Market and Sector Insight Fig 2 Tracks 3rd party device utilization and errors
  12. 12. 12 Confidential Provides Configurable, Automated, Real-Time Mapping Integration with Google Earth & Google Maps shows automated, real-time localization of devices, health workers, patient sessions, contact tracing; real-time, cross-correlated heat maps
  13. 13. 13 Confidential Transforming the Quality and Economics of Healthcare 10x Reduced testing errors by health workers 20x Increased epidemiologic accuracy 20x Reduced repeat patient visits 33% Reduced per-patient cost of care 100x More oversight data, at 15% of current cost 10x Increased compliance with protocols for care from 500,000 dataset uploads, 12 clients, 8 countries, 3 continents
  14. 14. Simple, Sustainable, Scalable Pricing Model 14 Confidential Subscription fees based on:  Volume of devices  Term of contract  Mix of readers vs tablets  Market  Average: 10 cents/patient Simple start, sustainable finish  No capital investment necessary  Technology transferred to client with zero-footprint infrastructure, mobile-first technical solution
  15. 15. 15 Confidential Transforming the Reach of Healthcare India: urban hospital South Africa: central lab Nigeria: remote clinic