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Neal Lesh
Computer science applications to improve health delivery in low-income countries.
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...
Outline
• BackgroundThe simplicity and complexity of global inequity
• Two examplesPatient record systems for AIDS treatmentMedical algorithms on handhelds
• Conclusion
Risk Factorfor surviving the Titanic.
0
10
20
30
40
50
60
70
1st 2nd 3rd
class of service
% s
urvi
ved
Poverty as a
Global Health
Simple Story$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$
Infant mortality: 5 per 1,000 births
Maternal mortality: 8 per 100K births
Life expectancy: 78 years
Infant mortality: 95 per 1,000 births
Maternal mortality: 500-1000 per 100K
Life expectancy: 45 years
300-540
57
69
Simple Story$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$
Simple Story$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
$$$$ Infant
mortality: 95 per 1,000 births
Maternal mortality: 500-1000 per 100,000 b
Life expectancy: 45 years
Simple Story
“We are the first generation that can end poverty.”
-Eveline Herfkens, UN Millennium Campaign
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
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.
Outline
• BackgroundThe simplicity and complexity of global inequity
• Two examplesPatient record systems for AIDS treatmentMedical algorithms on handhelds
• Conclusion
One year later
AIDS Treatment in Rural Rwanda
One year later
Improving Health Systems
One year later
Connecting to the Internet
Electronic Medical Record (EMR)
Patient MonitoringReports
Clinicians & Patients
Managers
EMR Staff
Paper forms
Program MonitoringReports
Funder & governmentreports
$
Re-allocate resources
Patient Monitoring
Missed-Visit List
ICT task: satisfy reporting requests
OpenMRS
• Open source framework for medical record systems
• www.openmrs.org
Data Quality
• Mistyped IDs• Missing &
conflicting data• Backlog
Potential solution: point-of-care systems
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
Outline
• BackgroundThe simplicity and complexity of global inequity
• Two examplesPatient record systems for AIDS treatmentMedical algorithms on handhelds
• Conclusion
Rural Dispensary in Tanzania
Standardized Care (IMCI)
Standardized Care (IMCI)
Standardized Care (IMCI)
10
15
20
25
30
35
1999-00 2001-02
An
nu
al
mo
rta
lity
ra
te
Morogoro (IMCI) Rufiji (IMCI)
Ulanga Kilombero
Tanzania: underfive mortality was 13% lower in the two IMCI districts
Source: Schellenberg J et al
Full IMCIin HF
End ofstudy
13% difference95% CI: -7%, 30%
Significant impact on stunting
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
Why Automate IMCI?
Why Automate IMCI?
• Improve adherence• Improve
supervision• Easier to update• More sophisticated
protocols• Reduced training
Field Work
Results to be published in CHI’08
How Automate IMCI?
Exploratory Study
• Pretesting & rapid iteration• Structured interviews• Observed trials w/
additional clinician to:– Ensure safety– Record adherence to IMCI– Record time
Viral Training
Key Findings
• Must be – Fast– Flexible– Improve adherence to IMCI
• Must address intentional deviation from IMCI– Temperature, respiratory rate– Advice
Adherence ResultsInvestigation
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
Triaging patients on treatment for AIDS
(Study ongoing in South Africa)
Counselors ask a series of questions leading to a patient assessment.
e-CTC for HIV screening
CommCare
Start House Hold Visit
Plan Day
Explore Data
Exit
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
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
Outline
• BackgroundThe simplicity and complexity of global inequity
• Two examplesPatient record systems for AIDS treatmentMedical algorithms on handhelds
• Conclusion
Conclusion
• Key points– Must understand context– Much potential, many challenges– Keep it simple
• Challenges– Evaluation, local ownership, I2I, duplication of
effort, …
Thank [email protected]