From computer scientist to global health techie: a preliminary report

1. From computer scientist to global health techie: a preliminary report Neal Lesh

2. Alerts for Pediatric AIDS meds • Pediatric review

3. Outline • Background: The simplicity and complexity of global inequity • Field reports: AIDS treatment program in urban Tanzania Social justice organization in rural Rwanda PDA research project in South Africa • Transition to discussion …

4. Simplicity: rich vs. poor

5. Simplicity: rich vs. poor

6. Simplicity: rich vs. poor

7. Simplicity: rich vs. poor Life expectancy: 78 years per 1000 births Infant mortality: 5 Maternal mortality: 8 per 100,000 births Life expectancy: 45 years Infant mortality: 95 per 1000 Maternal mortality: 500-1000 per 100,000

8. Simplicity: rich vs. poor Life expectancy: 45 years Infant mortality: 95 per 1000 Maternal mortality: 500-1000 per 100,000

9. Complexity • Corruption, careerism, tax write-offs • 5-star poverty alleviation meetings • 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

10. Outline • Background: The simplicity and complexity of global inequity • Field reports: AIDS treatment program in urban Tanzania Social justice organization in rural, Rwanda PDA research project in South Africa • Transition to discussion …

11. My last few years • Sep 2004: back to school • Jun 2005: off to Tanzania • Oct 2005: overland to Rwanda • Since Jan 2006: bouncing around among Tanzania, Rwanda, South Africa and New York

12. Tanzania

13. MDH • MDH= Muhimbili University + Dar Es Salaam + Harvard University. • US government AIDS treatment program, currently about 25,000 HIV+ patients. • Reason for going: they needed a new data person, because current was leaving.

14. MDH data capture • Doctors fill in paper forms for each client visit • Carbonless copy goes to HQ for double-entry • Data stored in Microsoft Access • Processed in SAS to produce useful reports • Patient monitoring • Program monitoring • External funders and government reports

15. Missed-Visit List

16. More alerts

17. One Page Patient Summaries

20. Issues • Mistyped IDs • Missing & conflicting data • Backlog • Efficiency & scaleability

21. Challenges • Missing or late lab results • Use of reports to improve decision making. • Detect important trends in data

22. Rwanda

23. Every situation different… • Tanzania -> Rwanda • AIDS treatment -> Social Justice • Urban -> rural

24. First Year Rwanda Milestones • Rwinkwavu is now a functioning district hospital

25. First Year Rwanda Milestones • Rwinkwavu is now a functioning district hospital

26. PIH Rwanda HIV & TB Scaleup

27. First Year Rwanda Milestones • Over 400 Community Health Workers (Accompagnateurs)

28. First Year Rwanda Milestones A food package provide for all at the start of ART and TB treatment

29. Milestones • Program on Social and Economic Rights (POSER). • Housing assistance • School fees (cost of school is subsidized for over 1450 children).

30. Milestones:Malnutrition Program 5 semaines plus tard

31. How old? 11 13 9

32. Overall ICT Mission • Develop and install OpenMRS: • An open source framework for medical record systems in low-income regions • Reducess duplication of effort • Fast-growing collaborative effort • Installations in Kenya, Rwanda, Lesotho, Tanzania, and Kenya • Join today! Come to meetings! • Or come to Rwanda to teach Java. Contact Christian (callen@pih.org) or me for details.

33. ICT task: keep the internet running

34. ICT task: manage data collection

35. ICT task: satisfy reporting requests

37. Lab System

38. Hard to get on top of it! • Hard to hold on, let alone make progress. • Pulled in a lot of directions. • Data quality a struggle • Data use a struggle • Might be close now... • Probably about to be the national standard…

39. South Africa

40. Screening on Mobile Device Patient goes home with meds, to return next month YES Patient doing well? Patient referred to nurse or doctor NO

41. Screening on Mobile Device

42. Shortage of Doctors Conclusion: The shortage of doctors and nurses requires that future expansion occur in rural clinics with most patient visits being managed by health workers with minimal training.

43. Plan • Currently validating interface & protocol • Double blind study in top-notch hospital clinics • Revising questions after first round • Next step: operationalizing system • Link to OpenMRS • Deploy in down-referral clinics • Remote supervision • Reports delivered to clinics

44. Integrated Management ofChildhood Illness (IMCI)

45. Potential benefits of point-of-care protocols • More consistent and accurate use of protocols • More sophisticated and dynamic protocols • Easier to update • Less training • Improved supervision & monitoring • Data collection

46. Discussion Some questions I don’t have answers to • Is there ‘real’ computer science to be done here? • Too much focus on health? What about water, education, economics, etc? • How do we evaluate if these systems are worth their cost?