1. ICT 4D CONFERENCE Title: Mobile Digital Diagnosis and Data Management By: Dr. Elias K. Sory, Director, Fio Health Ghana Ltd.

2. FIO HEALTH GHANA
Fio Health Ghana Ltd. has partnered with Fio Corporation of Canada to use Fionet in Ghana’s health care delivery system to enable high impact, high quality diagnosis of infectious diseases and real-time readily accessible data for health managers.
Directors:
Dr. Elias K. Sory, MD – Former Dir. Gen. Of GHS
Dr. Edem Adzogenu, MD – Sr. Adv. to Ministry of Health

3. Fionet Validation Fionet Accra Phase – GHS
Luminary deployment with GHS
over 150 health workers trained
over 50 sites deployed and functioning
over 20,000 patient encounters
Fionet Clinical Field Validation
US NIH Center of Excellence in Malaria, Colombia
The Global Fund, Colombian NIH, MOH
US Department of Defense, KEMRI
Ifakara Health Institute, Tanzania
Experience
7,500 patient sessions, 50 health workers, 30 sites
4 countries
Consistently successful

4. Two of the Biggest Infectious Disease Mgmt Problems
Clinical Workflow
Managers, Administrators, Funders, Public Health, Industry
Data Aggregation
Monitoring and Data Mining
Health Worker Guidance
Inadequate Care
Health Workers
Diagnostic Testing
Inadequate Data
Data Capture & Transmission
Infectious diseases are a leading cause of global death, disease, and economic disruption. According to WHO, we “stand on the brink of a global crisis in infectious diseases. No country is safe from them. No country can any longer afford to ignore their threat." According to National Institutes of Health, infectious diseases take an economic toll of $120BN/yr in the US alone; in economies with more prevalent infectious diseases the economic toll is far greater.
Yet, the setting where the vast majority of the world’s infectious disease patients are seen is where diagnosis is most error-prone and from where data – for resource allocation, evaluation and monitoring, surveillance, quality control, process improvement, and private sector investment - is least available. Most patients everywhere are seen not in central facilities, such as hospitals, but rather at “point of care”: decentralized facilities such as clinics, health centers, health posts, and offices.
Infectious disease management at point of care is substantially unoptimized; as a result, it is the source of substantial misdiagnosis, misdirection of resources, and misinformation. For example, in Africa, as much as $1 billion per year of anti-malarial drugs is given to sick patients who do not have malaria, a typical waste of human and economic potential in developed and developing countries alike.
This is due to inadequate quality of diagnostic testing and inadequate data capture by health workers on the ground. The root problem with diagnostic testing is that rapid diagnostic test strips are interpreted by eye, commonly resulting in field accuracy far below the performance rating of the test strips, of which 700 million have been sold in 2012, growing at 20%/year. The root problem with data capture is that health workers are just too busy delivering care to add any material effort to capture data, no matter how valuable the data is to stakeholders such as public and private health program managers, administrators, funders, policy makers, payers, insurers, investors, and industry. Point-of-care data, where planning and trends begin and where spending and outcomes have their end, is largely inaccessible.
The annual market opportunity for an integrated solution that addresses these two big problems at point of care – inadequate care and inadequate data - is potentially $25-50BN, encompassing all markets and economies.
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Public and private health managers worldwide are responsible for overseeing chains of dispersed clinics and health centers, employing large numbers of health workers who deliver healthcare.
Inadequate Care Delivery at Point of Care
Most current diagnostics are either accurate, expensive machines in central labs or inexpensive, error-prone test strips at point of care.
Point of care is wherever the health worker and patient meet, such as clinics, offices, health centers and health posts, pharmacies, emergency centers, or military field operations.
~700 million point-of-care test strips, called rapid diagnostic tests or “RDTs”, were sold in 2012 for infectious diseases, growing at 15-20%/yr worldwide. Read by eye, RDTs are prone to human error, commonly resulting in low field accuracy, contributing to significant waste through inappropriate care and misdirected resources. For example, in Africa $1BN/yr of antimalarial drugs are administered to sick patients who don’t have malaria.
The clinical workup (which questions to ask, tests to administer, and therapies to give) by health workers at point of care often fails to meet quality or efficiency standards known to their health program managers, who lack the means to readily monitor, supervise, address deficiencies, and disseminate evolving standards of practice to health workers at point of care.
Inadequate Data from Point of Care to Healthcare Managers and Funders
Millions of point-of-care procedures, diagnoses, and treatments are performed daily, with negligible quality data flowing back to health program managers, their supervisors, or their funders.
The current system does not capture accurate, timely point-of-care diagnostic, clinical, and demographic patient data. It does not capture health worker activity or outcomes of expended resources.
The result is a big gap between large annual expenditures and tracking, essential for public and private rationalization of resourcing and investment decisions: unknown patient data, diagnostic patterns, demography and epidemiology; unknown resource need and deployment detail; unknown health worker and clinic performance and activity, systemic inefficiencies and abuses; and, unknown opportunities.
Error-prone diagnostic testing
Ineffective clinical work-up and therapy
Negligible data capture and transmission, despite enormous information access
Incomplete, inaccurate, untimely data
Ineffective tracking and direction of resources, results, performance, epidemiology, demography, surveillance, accountability, …
Blind spending and investment

5. Readers, Tablets, Phones Web Portal
Cloud
Aggregates data, continually and automatically uploaded from Fio smart-devices at point of care
Delivers information services via web portal to managers, administrators, workers, funders, health agencies, patients
via local cell networks
via standard browsers
Readers, Tablets, Phones
for health workers at point of care
Web Portal
for managers & data stakeholders, anywhere
Automated diagnostic interpretation, workflow guidance, data capture
Gateway: for data mining, analyzing, reporting; and, for remotely managing health workers
Fio automated both diagnostic test interpretation and large-scale data capture and integrated them, using only existing infrastructure and usable by minimally trained personnel. To deliver this affordably, while retaining attractive margins, Fio adapted the recurring fee model common to cell phone carriers and the software-as-a-service industry.
The solution consists of: (1) handheld smart-devices that provide on-the-spot, automated, accurate reading of diagnostic tests, clinical guidance, and automated data capture; (2) cloud database to aggregate the data; and (3) web portals through which to mine the cloud database. The time-stamped and geo-tagged data thus gathered includes diagnostic, patient, demographic, epidemiological, logistical, environmental, and health worker activity data.
The solution enables high-quality healthcare delivery to individual patients while simultaneously converting routine diagnostic interactions, performed hundreds of millions of times yearly by health workers, into automated data capture events fully integrated with cloud information
Integrated m-phone, cloud computing, and bioassay technologies to transform infectious disease
The Fionet TM system improves healthcare delivery at point of care while simultaneously converting diagnostic tests, routinely performed hundreds of millions of times yearly, into automated data capture events. It connects mobile health to big-data capture and utilization. Fionet TM comprises:
Deki TM Reader a compact sidekick device for health workers at point of care in a broad range of settings
Automatically, accurately reads existing rapid diagnostic tests (RDTs) on the spot
Guides health workers through the workup and treatment of the patient
Deki TM application software, minus RDT interpretation, also runs on smartphones and tablets
Automatically, continually captures unlimited data (patient, diagnostic, demographic, workflow, environmental)
Continually uploads, via local cell networks, all data (geo-tagged and time-stamped) to airFioTM
Downloads Fio-qualified third-party mobile health apps
airFio TM Cloud Continuously grows a secure infectious disease database, on path to be world's largest in several years
Offers suite of real-time Fio Information Services to exploit the Fio Database
Enables communication among dispersed health workers, managers, and other stakeholders
Hosts third-party infectious disease apps and other resource materials
Spiri TM Web Portal
Secure gateway to airFio TM via any computer browsers (tablet, laptop, desktop)
Offers private and public clinic managers, administrators, and funders unprecedented access to:
- data capture, storage, retrieval, analysis; report generation; data export/import to other databases
- dissemination of clinical workup and treatment protocols, data capture forms, apps, alerts to Deki TM
- remote monitoring, guidance, quality control of workers, and communication with all stakeholders
- mining, mapping, surveilling, screening, analyzing global or regional aggregated, anonymized data
Fio Clinical PanelsTM (not shown) are proprietary test strips that can simultaneously detect multiple pathogens relevant to a clinical situation, and at an accuracy level that matches central labs

6. Consistent, Accurate RDT Results
Digital Diagnosis:
Consistent, Accurate RDT Results
RDT
Identification
RDT
Processing QC
Incubation
Timing
Interpreting RDT Results
Problem:
While manufactured to be chemically accurate, RDTs are read by eye, prone to human error in a circumstance affording little quality control, resulting in real-world field accuracy as low as 65% and contributing to significant waste through misdirected resources, mistreated patients, and wasted RDTs
Solution:
The Deki Reader provides automated reading of RDTs. Currently compatible with various commercially-available malaria RDTs, other disease targets to follow in short order (i.e., HIV, syphilis, hepatitis B, etc.)
The Deki Reader digitally replaces key RDT processing steps, where human error occurs:
Identifies RDT disease target and manufacturer, thus recognizing if the wrong test strip is inserted into cassette drawer
Will reject RDT if it was left to incubate longer than the manufacturer’s recommended time (monitored via the Deki Reader’s chronometer)
Images and identifies poorly processed RDTs (e.g., mistakes in the quantity or placement of blood and buffer)
Assures the RDT is optically analyzed in a controlled chamber
Renders an objective, automatic, accurate interpretation of the RDT
Trust in the accuracy of RDT results leads to a more rational use of drugs, significantly reducing costs and positively influencing the quality of care.
Auto-detecting RDT make/model
Accepting or rejecting RDT processing
Enabling accurate multiple patient throughput
Digitally analyzing RDT results

7. Capturing Records, Connecting Anywhere
Custom Health
Forms/Surveys
Easy-to-use
Data Entry
Clinical Patient
Demographics
…via any Android device
Deki Reader
Workflow
Guidance
Deki Tablet
Alerts /
Messaging
Problems:
The data captured at point-of-care is, in general, manually captured and aggregated by overloaded health workers and health managers. This leads to poor quality data, reporting delays, and lack of follow-up care. Service providers and managers are faced with diverse and duplicative data sources and reporting processes.
Communication between frontline health workers and managers is limited, impeding workflow guidance, training and adequate human resource management.
Solutions:
Fio has designed custom software to run on its Deki Readers or any Android device (smartphone or tablet) that is used for data capture by health workers at point-of- care. This software can be integrated with RDT diagnostics (i.e. with the Deki Reader), with other diagnostics (e.g., microscopy) or where no diagnosis is made at all (e.g., patient follow-up visits, surveys, immunization records, treatment recommendations, etc.)
Its data capture functionality prompts the health worker through complete clinical, demographic and survey forms that are remotely programmable by their health managers (e.g., public health reporting forms, insurance claim forms, etc.); data from these forms are automatically aggregated on Spiri leading to streamlined workflow, reduced errors, and timely reporting of high- quality data
The software can be easily integrated with existing HMIS systems
Via airFio, health program managers are continuously connected with frontline health workers in both urban and rural centres, enabling the implementation of training and quality control measures; dissemination of workflow guidance, treatment protocols, operational and business process guidance; and monitoring health worker activity for improved human resource management
Deki Phones and Tablets upload clinical and health worker activity data to airFio, where it is integrated with data from Deki Readers, and to which authorized health managers and other stakeholders have access via Spiri
Training
Deki Phone

8. Health worker connectivity:
Remote Configuration/Communication with Deki
Deki Management
Via Spiri, managers track/administer their fleets of Deki devices:
Locations, activities, configurations, problems, user permissions, alerts, …
Shut down, reset, or group Deki devices
Multidirectional communication for managers and health workers via Deki devices & Spiri

9. Automated Reporting of Point-of-Care Data
Process Improvement:
Automated Reporting of Point-of-Care Data
Data
Reports
Reports can be flexibly configured to present data about devices, users, diagnostic results, demographics, surveys, time, geo-location, ...

10. Process Standardization RDT image captured in the record
Example: Monitoring service delivery
RDT image captured in the record
Managers identify deviations from protocol, correlate diagnostic activity to drug dispensing
Managers track worker activity and performance patterns over time
RDT images are captured and routinely included as part of the record
Managers assess RDT processing skills of healthcare workers and over-read RDTs if necessary

11. Pricing Model
Deki : no capital equipment barrier; rental pegged to usage
Spiri: fee per dataset upload for information services; uploads pegged to usage
“dataset” is the data associated with one patient session, which is uploaded at once
fees organized to fit into existing data budgets… not from diagnostic budget
pricing model designed for sustainability
Purchase order a three-year contract