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Namitete, Malawi
St. Gabriel’s Hospital
250,000
100
2
people
miles
doctors
phones
100
$10each
Injury
Emergency Care
CHW alerts the clinic
Clinic dispatches resources
Mahmud N, Rodriguez J, Nesbit J. A text message-based intervention to bridge the healthcare communication gap in the rural developing world. Technol Health Care. 2010 Jan; 18(2): 137-44.
Injury
Emergency Care
CHW alerts the clinic
Clinic dispatches resources
Mahmud N, Rodriguez J, Nesbit J. A text message-based intervention to bridge the healthcare communication gap in the rural developing world. Technol Health Care. 2010 Jan; 18(2): 137-44.
150 patients over 6 months
Patient Tracking
Patient misses appointment
CHW receives alert
CHW locates and checks in with patient
CHW reports patient’s status
Mahmud N, Rodriguez J, Nesbit J. A text message-based intervention to bridge the healthcare communication gap in the rural developing world. Technol Health Care. 2010 Jan; 18(2): 137-44.
Patient Tracking
Patient misses appointment
CHW receives alert
CHW locates and checks in with patient
CHW reports patient’s status
Mahmud N, Rodriguez J, Nesbit J. A text message-based intervention to bridge the healthcare communication gap in the rural developing world. Technol Health Care. 2010 Jan; 18(2): 137-44.
2100 hours saved$3,500 saved
Management
Mahmud N, Rodriguez J, Nesbit J. A text message-based intervention to bridge the healthcare communication gap in the rural developing world. Technol Health Care. 2010 Jan; 18(2): 137-44.
Stock Levels
Clinics upload reportsfor vital stock levels
Reports are monitored at central office
Restocking based on need
STOCK LEVELS
Symptom Monitoring
Mahmud N, Rodriguez J, Nesbit J. A text message-based intervention to bridge the healthcare communication gap in the rural developing world. Technol Health Care. 2010 Jan; 18(2): 137-44.
Symptom Monitoring2x number
of TB patients
Mahmud N, Rodriguez J, Nesbit J. A text message-based intervention to bridge the healthcare communication gap in the rural developing world. Technol Health Care. 2010 Jan; 18(2): 137-44.
Image courtesy Logan Abassi, UNDP
80,000 SMS
“My name is J___ ____ my brother is working in Unicef and I live in ____ I have 2 people that is still alive
under the building still ! Send Help!”
Graphic by Abraham Flaxman
What do we have?
Image courtesy of Global Cycle Solutions
Images courtesy of http://www.safaricom.co.ke
Mobile money
Mobile + radio
Photo credits: Kate Kelly, developingradiopartners.org
50% in West Africa
40% on mobile
Real systems
diverse low end phones
SIM apps
Images courtesy of the Fletcher Lab at UC Berkeley, Diagnostics for All, Dr. Ozcan’s lab at Image from givengain.com
MMS-based diagnostics
Image from http://www.cs.jhu.edu/~jason/465/
Machine learning
2,364 people accessing emergency care.
10,795 patients remaining in care across 3 infectious disease treatment and prevention
programs.
858 new TB patients identified and entered into care.
2,690 health workers reporting stocks 112x faster and 4x cheaper, serving
270,800 people.
1,036 health workers doing remote treatment consults 100x faster, serving
71,820 people.
356,637 patients
1.78 million people
500,000 cell phones per day
“Cell Phones #2” by Chris Jordan, Atlanta 2005
hopephones.org
OLD PHONES SAVE LIVESHope Phones’ first pilot project distributed cell phones to community health workers in 100 rural villages in Malawi, saving thousands of dollars in travel and hospital costs and doubling the number of patients treated for diseases such as tuberculosis.
Each donated phone will be refurbished and used to purchase appropriate, usable cell phones for community health workers in medical clinics in over 30 countries around the world.
When you donate your old cell phone to Hope Phones, the road becomes less traveled by medical staff in Malawi.
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300,000
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