innovation to improve children’s health: lessons learnt
TRANSCRIPT
©T
dh/O
llivie
r G
irard
– B
urk
ina F
aso
Innovation to Improve Children’s Health:
Lessons learnt from IeDA piloting in Burkina Faso
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• 1 out 10 children in Burkina Faso dies from treatable diseases
(Malaria, pneumonia, diarrhea, etc) before reaching age 5
• IMCI (Integrated Management of Childhood Illness), a WHO
protocol applied in Primary Healthcare Facilities (PHF) has been
designed to solve the problem 20 years ago
• HOWEVER it suffers from poor implementation: lack of
equipment, lack of adequate training for MoH staff, complex
protocol to implement, lack of reliable data, etc.:
Only 32% of children are seen in IMCI consultations
What about leveraging ICT to improve IMCI implementation
and improve quality of care for children?
How to Reduce High Child Mortality?
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IeDA Virtuous Circle: 4 Components
• Improve service
management
• Measure individual
performances
• Identify individual training needs
• Reduce training cost
• Stronger training impact by individualizing training offer and follow-up
• Improve data quality
• Help identify most frequent errors
• Identify dysfunctional health centers
• Improve diagnosis and treatment accuracy
• Reduce paper work
E-Diagnostic Data
Management
Quality Improvement and Coaching
E-Learning
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IeDA in Burkina Faso Today
620+ PHFs
(1/3 of Burkina Faso)
1.5 million patients registered
(7,5% of total population)
180,000+ consultations/month,
2.5 million to date
2,600+ current users with
over 80% of patient under-5-
consultations made with the
tool
Tdh and Burkina Faso MoH co-
writing a transfer strategy to
take place in 2019-2020
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How Is Data Collected?
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REC (Registre Electronique de Consultation) App:
Digital job aid and data collection
Digitized IMCI protocol and
patient registration: Automated
diagnostic and treatment
Data Management: Report on
aggregated data available on
the tablet
Data sent to the server (2G or 3G)
PHFs equipped with tablet with a
mobile application installed used
during the consultation
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Coach App:
Assessment Tool and Data Collection
Digitized monitoring: Tool to
assess both clinics and Health
Workers during a consultation
Data sent to the server (2G or 3G)
DTMs are equipped with tablets
and a mobile app
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(Server)
PHFs
Dashboards
(District/National levels)
Research
(MoH server)
Processed
data
Raw data
Processed
data for
reporting
Data linked
to 60
indicators
Data for scientific
research
RBF indicators*
Processed
data
IeDA Data Management Flow
*RBF: Result Based Financing:
World Bank program to
financially incentivize HWs
based on their performances
REC
(Consultation)
Coach
(Monitoring)
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IeDA Dashboards
PHFs REC
(Consultation)
Coach
(Monitoring)
(Server)
Dashboards
Quality
Assurance (QA)
Dashboards
Quality
Insurance (QI)
Dashboards
Common
Mistakes
Dashboards
Post Training
Raw data
Processed
data Processed
data
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How Is Data Used for
Decision Making?
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Data for Decision Making (Clinic Level)
Number of consultations per HCW in a PHC
Consultation data:
• Performance per PHFs and
HWs
• Disease prevalence:
• Malaria
• Diarrhea
• Pneumonia
• Etc.
Data used for reporting and
PHFs management
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Data for Decision Making at the District Level (1/2)
Data on IMCI Danger Signs (Titao district QA dashboard)
Provide an overview to the District Management Teams
(DTMs) on PHFs and HWs performances
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Data for Decision Making at the District Level (2/2)
Malaria prevalence among children diagnosed with fever per clinic
(Yako district, QA dashboards)
The DTMs can identify outliers more easily and act: phone call
for an immediate action, followed by an inspection
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Data for Decision Making at the National Level 1/2
Web dashboard aggregating data from all districts:
Provide decision makers with a situation overview to
identify issues at the district level
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Data for Decision Making at the National Level 2/2:
Feeding the Health Information System (HIS)
(Server)
Data on 60 indicators
defined by the MoH
IeDA data is integrated into the HIS :
• 60 indicators defined by the MoH are
fed with IeDA data
• Large dissemination within the
MoH: all stakeholders at the national
and regional levels can access the
data
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Data for Capacity Building
Dashboards on most common mistakes made by HWs in consultation
(Solenzo district, Most Common Mistakes dashboards)
The DTMs can identify the most common mistakes made by
HWs and tailor trainings, QI sessions and e-learning content
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Data for Decision Making:
Performance Management E-learning management platform: example of one HW performances
Identify HW poor performances to assign adequate training content,
in this case a training session on malaria
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Data Management
Future Developments
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Example of data visualization with Tableau
Improve Data Management for IeDA with Tableau
• Partnership with the
Tableau Foundation on
data management
• Web dashboards
automatically updated
• Improved visualization to
facilitate understanding
and analysis
• Increased data usage in
decision-making process
Get users addicted to data!
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Ambitions: Artificial Intelligence as a job-aid
1. Identifying outliers
immediately:
• PHF: Alert HW when making a
diagnostic and treatment
• District: Point out HWs and
PHFs with out of the norm results
• National: Point out districts with
out of the norm results
2. Offer predictive analysis for:
• Consultation peak periods
• Epidemiological surveillance
• Stock management (drugs)
Help stakeholders make better decisions more quickly by:
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Lessons Learnt &
Recommendations
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IeDA Existing Challenges
1. Getting MoH stakeholders to use data for all their
processes and decisions: Data usage is still partial and not
systematic
2. Technical difficulties in managing huge data amount:
Excel dashboards cannot deal with such an amount, forcing
us to adopt temporary solutions
3. Transfer process to the MoH: The project transfer will start
in 2019, including capacity building for MoH staff: can they
foster a data management culture within their organization?
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Lessons Learnt
1. It takes time, effort and resources to put the seeds of a
data culture within an organization
2. Use peer pressure to encourage data usage and start at
the top: «Waterfall pressure»
3. Design data management for scale:
1. Use tools and technologies which can be scaled
2. Define needs at the beginning of the project
4. Build simple, easy to use tools and reduce the number
of indicators as much as possible
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E-Learning
Individualized learning sessions on tablets or smartphones
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IeDA Added Value: Being a Platform
IeDA is used as a base upon which other applications,
processes or technologies are developed or implemented
Use IeDA’s tablet to deploy an
application in the field
Use IeDA’s data for research Test additional devices for
diagnostic improvements
IeDA
Applications
Technical add-ons
Data research
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Disaster Risk Reduction system (ECHO funded):
• Pilot in Burkina Faso (2018-2021): 105 clinics and 591 villages
• Create an alert and surveillance system for infectious
diseases and natural disasters:
• Report events in real time
• Make data available via web dashboards
• Inform stakeholders immediately via SMS
• Provide reliable data for monitoring
IeDA for Epidemiological Surveillance
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IeDA: UHC Cost Control Tool in Burkina Faso
Universal Healthcare Coverage
(UHC) being implemented:
Need for:
• Consultation and prescription
cost control
• Reliable data for the UHC
information system
IeDA can provide all the
information!
Prescription cost of an IMCI consultation estimated by the REC
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IeDA: Supports to Public Records Office (PRO)
REC additional value:
Through IMCI consultations, the REC
has more children registered than the
local PRO: Potential support:
1. Increase the number of children
registered in the PRO by bridging
the gap between the PHF and the
local administration
2. Ensure user’s identity integrity by
testing new data protection
technologies (Blockchain; Bubble
tag)
Patient Personal data entered in the REC