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Neal lesh-1202742298252135-3 (5)

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Neal lesh-1202742298252135-3 (5)

  1. 1. Neal Lesh Computer science applications to improve health delivery in low-income countries.
  2. 2. My Story Mid-thirties computer researcher seeks more fulfilling career. Goes back to school then off to Africa. Discovers things are more simple and more complex than he originally imagined. Can't imagine doing anything else...
  3. 3. Outline • Background The simplicity and complexity of global inequity • Two examples Patient record systems for AIDS treatment Medical algorithms on handhelds • Conclusion
  4. 4. Risk Factor for surviving the Titanic. 0 10 20 30 40 50 60 70 1st 2nd 3rd class of service %survived Poverty as a
  5. 5. Global Health
  6. 6. Simple Story $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $ Infant mortality: 5 per 1,000 births Maternal mortality: 8 per 100K births Life expectancy: 78 years Infant mortality: 95 per 1,000 births Maternal mortality: 500-1000 per 100K Life expectancy: 45 years 300-540 57 69
  7. 7. Simple Story $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $
  8. 8. Simple Story $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$$$$ $$$$$$$$$$$$$ $$$$ Infant mortality: 95 per 1,000 births Maternal mortality: 500-1000 per 100,000 Life expectancy: 45 years
  9. 9. Simple Story “We are the first generation that can end poverty.” -Eveline Herfkens, UN Millennium Campaign
  10. 10. Complexity • Corruption, careerism, tax write-offs • 5-star poverty alleviation meetings • Unintended consequences, e.g., paying volunteers • Imperialism & foreign experts “If you want to build a ship, don't drum up people to collect wood and don't assign them tasks and work, but rather teach them to long for the endless immensity of the sea.” – Antoine de Saint-Exupery
  11. 11. Information as Care • Study: rigorous application of standard treatment protocols reduced in-hospital mortality in children’s malaria cases by 50% • Clinician’s complaint: where are my lab results?! • Patient Knowledge Example: five danger signs for seeking care during and after labor.
  12. 12. Outline • Background The simplicity and complexity of global inequity • Two examples Patient record systems for AIDS treatment Medical algorithms on handhelds • Conclusion
  13. 13. One year later AIDS Treatment in Rural Rwanda
  14. 14. One year later Improving Health Systems
  15. 15. One year later Connecting to the Internet
  16. 16. Electronic Medical Record (EMR) Patient Monitoring Reports Clinicians & Patients Managers EMR Staff Paper forms Program Monitoring Reports Funder & government reports $ Re-allocate resources
  17. 17. Patient Monitoring
  18. 18. Missed-Visit List
  19. 19. ICT task: satisfy reporting requests
  20. 20. OpenMRS • Open source framework for medical record systems • www.openmrs.org
  21. 21. Data Quality • Mistyped IDs • Missing & conflicting data • Backlog Potential solution: point-of-care systems
  22. 22. Challenges & Opportunities • Keep up with demand • Increased impact on decision making – Inform to Improve (I2I) teams • Integration of lab and pharmacy components • Detecting important trends in data
  23. 23. Outline • Background The simplicity and complexity of global inequity • Two examples Patient record systems for AIDS treatment Medical algorithms on handhelds • Conclusion
  24. 24. Rural Dispensary in Tanzania
  25. 25. Standardized Care (IMCI)
  26. 26. Standardized Care (IMCI)
  27. 27. Standardized Care (IMCI)
  28. 28. 10 15 20 25 30 35 1999-00 2001-02 Annualmortalityrate Morogoro (IMCI) Rufiji (IMCI) Ulanga Kilombero Tanzania: underfive mortality was 13% lower in the two IMCI districts Source: Schellenberg J et al Full IMCI in HF End of study 13% difference 95% CI: -7%, 30% Significant impact on stunting
  29. 29. Deploying IMCI • IMCI – Shown to reduce mortality and morbidity – Adopted by ~100 countries • But uptake not as good as hoped – Training expensive – Correct use tapers off over time – Supervision challenging
  30. 30. Why Automate IMCI?
  31. 31. Why Automate IMCI? • Improve adherence • Improve supervision • Easier to update • More sophisticated protocols • Reduced training
  32. 32. Field Work Results to be published in CHI’08
  33. 33. How Automate IMCI?
  34. 34. Exploratory Study • Pretesting & rapid iteration • Structured interviews • Observed trials w/ additional clinician to: – Ensure safety – Record adherence to IMCI – Record time
  35. 35. Viral Training
  36. 36. Key Findings • Must be – Fast – Flexible – Improve adherence to IMCI • Must address intentional deviation from IMCI – Temperature, respiratory rate – Advice
  37. 37. Adherence Results Investigation Current practice adherence e-IMCI adherence p-value Vomiting 66.7% (n=24) 85.7% (n=28) - Chest indrawing 75% (n=20) 94.4% (n=18) - Blood in stool 71.4% (n=7) 100% (n=3) - Measles in the last 3 months 55.6% (n=9) 95.2% (n=21) < 0.05 Tender ear 0% (n=1) 100% (n=5) - All 61% (n=299) 84.7% (n=359) < 0.01
  38. 38. Triaging patients on treatment for AIDS (Study ongoing in South Africa)
  39. 39. Counselors ask a series of questions leading to a patient assessment. e-CTC for HIV screening
  40. 40. CommCare Start House Hold Visit Plan Day Explore Data Exit
  41. 41. House Hold Visit (Task Queue) 000:04:56 Register Birth Investigate Diarrhea of Sick Child Review malaria bed nets Topic of month: nutrition during pregnancy END VISIT
  42. 42. Day Planning MKWERA : TB Referral (2 wks) MKEA: Severe diarrhea (3 days) CHUMA: late HH visit (3 months) KAIGILE: routine HH visit MGANDA: routine HH visit EXIT
  43. 43. Outline • Background The simplicity and complexity of global inequity • Two examples Patient record systems for AIDS treatment Medical algorithms on handhelds • Conclusion
  44. 44. Conclusion • Key points – Must understand context – Much potential, many challenges – Keep it simple • Challenges – Evaluation, local ownership, I2I, duplication of effort, …
  45. 45. Thank you! neal@equalarea.com Inshuti Mu Buzima Partners In Health PO Box 3432, Kigali, Rwanda

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