This document discusses transforming decentralized healthcare through an integrated care and insight system. It highlights that 95% of patient encounters occur in decentralized facilities but 95% of health data comes from centralized facilities, creating a major disconnect. The system aims to enable health workers to deliver care on par with experts, provide stakeholders with real-time tracking and analytics insights, and use care data to drive improved insights which then improve care. It provides examples of how the system has reduced errors, increased compliance with protocols, and lowered costs while dramatically increasing oversight, epidemiological accuracy, and the reach of healthcare.

1. 21 October 2016 Confidential
TRANSFORMING THE REACH,
ECONOMICS AND QUALITY OF
DECENTRALIZED HEALTH CARE
CARE
DATA

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

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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

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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

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Mobile Point-of-Care Full Companion
Automated
Workflow Guidance │ Universal Rapid Test Reading │ Connectivity │ Data Capture

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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

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Capture last-
mile data from
care processes
Extract
multi-level
insights
Inject insights
into
care processes
Care Drives Insights, Insights Drive Care

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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

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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

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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

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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

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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

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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. Simple, Sustainable, Scalable Pricing Model
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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

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Transforming the Reach of Healthcare
India: urban hospital South Africa: central lab Nigeria: remote clinic

16. Q4 2016 Confidential
THANK YOU
CARE
DATA
INTEGRATING INSIGHT FLOW AND CARE FLOW