Nadim Mahmud Co-founder Research Director @nadimmahmud @medic
There is a 4.4 million global health worker shortage - WHO
 
 
 
 
 
 
<ul><li>Cell phones are becoming ubiquitous </li></ul>
 
 
 
 
73% of all mobile users are in the developing world By 2012, 50% of individuals living in remote areas in the world will h...
 
 
250,000 100 2 people miles doctors
 
15
 
 
 
Text message network
 
 
 
Injury Emergency Care CHW alerts the clinic Clinic dispatches  resources Mahmud N, Rodriguez J, Nesbit J. A text message-b...
$3,500 saved
Patient misses  appointment CHW receives alert CHW locates and  checks in with patient CHW reports  patient’s status Mahmu...
2x number  of TB patients Mahmud N, Rodriguez J, Nesbit J. A text message-based intervention to bridge the healthcare comm...
 
Mahmud N, Rodriguez J, Nesbit J. A text message-based intervention to bridge the healthcare communication gap in the rural...
Impact in six months: 1. Saved $3,500 in motorcycle fuel 2. Saved 2,100 staff hours 3. Doubled enrollment in Tuberculosis ...
 
FrontlineForms
 
 
 
Referrals
STOCK LEVELS Clinics upload reports for vital stock levels Reports are monitored at central office Restocking based on nee...
 
Synergy of:  mobile + (traditionally) non-mobile tech
PatientView
 
 
 
 
Photographs courtesy of Dr. Ozcan’s laboratory, UCLA and Science LUCAS Prof.  Aydogan Ozcan, UCLA MMS + Diagnostics
 
Synergy of:  mobile + social media
Haiti: 4636 Project
 
 
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 bu...
 
Image from EFE
Graphic by Abraham Flaxman
 
Help create connected, coordinated health systems that save lives.
 
[email_address] twitter: @nadimmahmud
ndimmafuna manthwala (‘I currently need medicine’) ndimafuna mantwala ndi-ma-fun-a man-twala ndi -ma- fun -a   man - twala...
 
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Medic Mobile_Columbia University

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Medic Mobile presentation at Columbia University, March 2011

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  • Use low-cost mobile technology to create connected, coordinated healthcare systems that save more lives.
  • Countries with health worker shortages
  • AIDS prevalence (proportionality map)
  • Tuberculosis
  • Malaria endemicity map. These maps overlay very well with those countries that have health worker shortages.
  • Countries with health worker shortages
  • The 5 billionth cell phone subscriber was recorded in July, btw. In stark contrast to access to Internet at ~10% in Malawi. Computer literacy is also very much lower than mobile literacy in Malawi.
  • Our flagship pilot was in Namitete, Malawi
  • Started work in Malawi at St. Gabriel’s Hospital where...
  • 2 doctors serve 250,000 people spread 100 miles in every direction. St. Gabe’s typifies the struggle of the health worker shortage.
  • Around St. Gabriel’s 500 community health workers work in remote villages to help decentralize care, but volunteers like Dickson walk 40 miles each way to hand-deliver updates on patients. adherence rates suffer, clinicians are unaware of patient statuses, immobile patients cannot receive emergency care, remote health workers lack support, new illnesses are not identified
  • CHW empowerment - when they aren’t paid with money…
  • Expanded to 75 CWS during next 2-3 weeks. Will expand to 50 more in next 2 months.
  • Impact -- Patients with urgent needs receive emergency care.
  • Impact -- More patients remain in treatment programs, emergency transport and home-based care teams respond to priority cases, less resources are spent following up on defaulting patients.
  • And the cost to run the program was only $500 (SMS text messages)
  • Qualitative outcome: empowerment
  • Translated into 15 languages thus far.
  • Impact -- Fewer patients ‘fall through the cracks,’ referral clinics are prepared for referred patients, more patients begin and remain in treatment.
  • Impact -- Fewer stockouts, less waste, more patients receive vital drugs.
  • Medic has expanded since our inception to 11 countries.
  • Light-weight medical records system that can accept forms!
  • How is it being used? Being piloted in Mali as a full-fledged records system for the patients. Also used to automate SMS reminders for vaccines in India.
  • Vaccine project in Kurnool, India
  • Crisis mappers based out of boston, montreal, and other places. Mapping and communicating information. 4636 was the channel that people could use to communicate what was happening/needed.
  • 80,000 SMS messages processed in 1 month
  • 1500 people all over the world helped translate messages from Haitian creole. Translated, categorized, and geomapped messages. Then these structured tags were passed onto Patrick Meier’s crisis mapping team for secondary processing and distribution.
  • There was no 911 system. 4636 was the way to communicate urgent needs.
  • Received about 200 text messages in a day from this IDP camp (~2500 people here). Needed food and water.
  • Get involved at Hope Phones- you can donate your old cell phones to us- they get refurbished, resold, and we use the proceeds to buy appropriate phones for our pilot sites.
  • Transcript of "Medic Mobile_Columbia University"

    1. 1. Nadim Mahmud Co-founder Research Director @nadimmahmud @medic
    2. 2. There is a 4.4 million global health worker shortage - WHO
    3. 9. <ul><li>Cell phones are becoming ubiquitous </li></ul>
    4. 14. 73% of all mobile users are in the developing world By 2012, 50% of individuals living in remote areas in the world will have mobiles The fastest growth is projected to occur in Asia and Africa
    5. 17. 250,000 100 2 people miles doctors
    6. 19. 15
    7. 23. Text message network
    8. 27. 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
    9. 28. $3,500 saved
    10. 29. 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. 2,100 hours saved Patient Tracking
    11. 30. 2x 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. Symptom Monitoring
    12. 32. 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. Management
    13. 33. Impact in six months: 1. Saved $3,500 in motorcycle fuel 2. Saved 2,100 staff hours 3. Doubled enrollment in Tuberculosis treatment program 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.
    14. 35. FrontlineForms
    15. 39. Referrals
    16. 40. STOCK LEVELS Clinics upload reports for vital stock levels Reports are monitored at central office Restocking based on need Stock Levels
    17. 42. Synergy of: mobile + (traditionally) non-mobile tech
    18. 43. PatientView
    19. 48. Photographs courtesy of Dr. Ozcan’s laboratory, UCLA and Science LUCAS Prof. Aydogan Ozcan, UCLA MMS + Diagnostics
    20. 50. Synergy of: mobile + social media
    21. 51. Haiti: 4636 Project
    22. 54. 80,000 SMS
    23. 56. “ 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!”
    24. 58. Image from EFE
    25. 59. Graphic by Abraham Flaxman
    26. 61. Help create connected, coordinated health systems that save lives.
    27. 63. [email_address] twitter: @nadimmahmud
    28. 64. ndimmafuna manthwala (‘I currently need medicine’) ndimafuna mantwala ndi-ma-fun-a man-twala ndi -ma- fun -a man - twala ndi -fun man-twala (“I need medicine”) Category = “Request for aid” 1) Normalize spellings 2) Segment words 3) Identify predictors Auto-categorization – the process 1 in 5 classification errors with raw messages 1 in 20 classification error post-processing. Improves with scale.

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