This document discusses data quality and use in immunization programs and the role of information and communication technology (ICT). It provides perspectives from JSI on improving routine data analysis and use at all levels for decision making. JSI emphasizes building on existing data tools but incorporating user-appropriate technology that allows bottom-up reporting and local data use. Examples are provided of countries that have integrated people, processes and tools through electronic logistics management information systems (eLMIS) to better summarize and generate immunization data electronically. The document also discusses the need for training health workers in data use, ensuring data quality and technology skills, and linking immunization data with supply chain management and community data.

1. DATA QUALITY AND USE
(IMMUNIZATION AND
ICT CONTEXT)
​Lora Shimp, Senior ImmunizationTechnical
Officer
(contributions:MuhammadTariq,Alpha
Nsaghurwe,Ousmane Dia)
​Using InformationandCommunication
Technology to Improve Immunization
Programs
​Istanbul,11-13 November 2014

2. 2|
JSI perspective on
data
• Improve routine (as possible)
data analysis, use, and feed-
in/feedback at all levels for
decision making
• Data as a “culture”,
particularly at operational
level
• Triangulation – routine tools,
surveys, mapping,locally-
generated,trend analysis, etc

3. 3|
JSI perspective on
data
• Visualization and user-
friendly/adapted (e-system
technologies;paper-based
sometimes also needed)
• Experience in over 30
countries for over 35 years –
technical support in
immunization,RMNCH,
logistics, technology and
software development, M&E

4. 4|
Immunization
register
Tickler file
Child
health
card
Tally
sheet by
antigen
Stock ledger
Relevance of existing
data tools
​Existing EPI data are usable & needed,but have
different purposes;some redundancy
​Important to build on what is working but
incorporate technology that is also:
• user-appropriate
• bottom-up
• incorporating feed-in mechanisms for local
data use, decision-making,and quality
reporting
• built with room-to-grow,as technology
advances

5. 5|
However: How to adapt to & keep-up with technology?
Use and adaptation
of data in the field
​Immunization data are
already being
consolidated,summarized,
and trends analyzed at
facility and community
levels.

6. 6|
Hospitals HC DSP
√ √ √
√ √ √
√ √ √
√ √
√
√ √
√ √ √
Service Delivery Point
R&R
ARVs
R&R
ILS
NTLP
TB
IVD
R&R
labs
R&R
HIV tests
MSD ERP
EPICOR
Shipments
Medical Store Department
OrdersRequisitions and Reports (R&R)
District
R&R
R&R
R&R
eLMIS
R&R
ILS-G
Region
LMU
The “data on the wall” can be useful and are now able to be more easily summarized & generated electronically (not just by hand)
Integrating people, processes and tools - eLMIS

7. 7|
5000+ HF
covered
Vaccine
Module
March 2015
Adapted
platforms for
data collection
(e.g.web, mobile
phone)
Tanzania eLMIS :
Where are we?

8. 8|
Vaccines
lmis.gov.pk
VSSM
CCEM 2
Paper
based
SDMS
LMIS
Inventory
Management
Routine
Immunization
Campaigns
Cold Chain Equipment
Management
vLMISIHR
Inventory
Management
Consumption
Reporting Paper
based
Paper
based
Inventory
Management
Consumption
Reporting
Paper
based
Paper
based
ContraceptivesTuberculosis
Online
lmis.gov.pk
- Includes policy, operations and system implementation guidance
PAKISTAN: One
web based IS for
three supply chains

9. 9|
vLMIS – Better
insight through
data
​with inclusive desk and field monitoring –
assessment,planning and implementation
​ (includes Change Management Board,Helpdesk,
GoP & donors)

10. 12|
• Training – in-service data use and
influence pre-service: standardized
immunization curriculum for all
medical & training institutes;agreed
data competencies (e.g.exit exams)
• Quality data & technology savvy –
• follow up through review
meetings and supportive
supervision;
• “professionalize” data managers
(e.g. statisticians,build analytical
and managerial capacity,
technology skills)
• appreciation of good and
consistent data performance
(certificates,exchangevisits,
asset-based review/learning)
What progress is
needed in other
areas to bring about
progress in data
quality and use?

11. 13|
• Supply chain – link stock management
data; eLMIS
• Community – build capacity for HWs
and mobilizers to compare and use
data
What progress is
needed in other
areas to bring about
progress in data
quality and use?

12. Thank you