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Adapting Data Quality Assurance
Approaches and Tools
to Meet Local Needs
Stephanie Mullen
MEASURE Evaluation
End-of-Phase-III Event, May 22, 2014
Why Do We Care
About Data Quality?
UNAIDS “Organizing
Framework for a Functional
National HIV M&E System”
Data Quality Tools
Data Quality Audit Tool Routine Data Quality Assessment Tool
Organization The Global Fund, USAID,
MEASURE Evaluation,
2008
MEASURE Evaluation
Purpose Assess data accuracy,
reporting performance,
and strengths and
weakness of underlying
M&E system that
generates the data
Streamlined version of the DQATool that is used
to verify the quality of reported data for key
indicators at selected sites and assess the ability
of the data management system to collect,
manage, and report high quality data
Uses Used by GF, USAID and
others to conduct
independent data quality
audits of their program
Used as a self-assessment tools by programs to
assess the quality of their data and use the
findings to develop action plans to strengthen
their data management and reporting systems
Languages English, French, Spanish,
Portuguese
English, French, Spanish, Portuguese
4
Additional Data Quality Tools
 Multi-Indicator
RDQA Tool
 Longitudinal
RDQA Tool
Applications of DQA/RDQA
 Botswana
 Suzanne Cloutier
 Tanzania
 Karen Foreit
Country Experiences
Adapting Data Quality Assurance
Approaches and Tools to Meet
Local Needs in Botswana
Suzanne Cloutier, Sergio Lins
MEASURE Evaluation
End-of-Phase-III Event, May 22,
2014
Data Quality Assurance Approach
Objective
Routine Monitoring
(all health programs)
Sampling
Purposive
Data Collectors
 Health Programs
 District Health
Management
Teams (DHMT)
Data Users
 Health Programs
 DHMTs
 Service Delivery
Sites
Deliverables
DataQuality
StandardOperating
Procedures(SOP)
Routine Data
Quality
Assessment
(RDQA) SOP
Botswana-RDQA
Tool
(B-RDQATool)
B-RDQATool
User Manual
Data Quality
Training
Curriculum
B-RDQA Tool Consultative
Workshop
April 2012
SOP Consultative Workshops
June 2012
Data Quality Training Workshops
Nov 2012 Apr 2013
Sharing Our Process
Global Maternal Health
Conference 2013
American Public Health Association
Annual Meeting 2013
Keys To Success
MoH
Champion
Country
Ownership
Decentralization
Evidence of Success
• M&E Officers conduct RDQAs
• Present results to District Health
ManagementTeams
District
• M&E Officers presented findings
from data quality assessments
• Included action plans
National M&E
Forum
• Formalize RDQAs as a routine
activity for districts
National Health
M&E Plan
Evidence of Success
Adapting Data Quality Assurance
Approaches and Tools to Meet
Local Needs in Tanzania
Karen Foreit, Mari Hickmann, Zaddy Kibao,
Dawne Walker, and Willis Odek
MEASURE Evaluation Phase III EOP, May 22, 2014
MEASURE Evaluation in Tanzania
Strengthen M&E
systems and capacity
 Improve data quality
 Enhance individual and
organizational capacity
 Promote data for decision
making
DQA for M&E Capacity-building
 New sampling
procedures
 New instruments
 Tailored training
 Measure change
 Stratify sites:
 By size (large vs. small) and
 By location (close to vs. far
from regional office/HQ)
 Select from all strata
New Sampling Procedures
New Data Collection Instrument
Community Trace
and Verify
 Visit “claimed”
beneficiaries
 Ask what services
they received
 Compare answers
to activity reports
No more “M&E 101”!
Tailored Capacity-building
 Prioritize problems
identified by DQA
 Group participants with
common problems
 Follow group training
with individualized
mentoring
Empiricalevidenceof
projectsuccessand/or
continuingchallenges
Measure Change
 Repeat DQA
 Focus on areas
selected for
capacity-building
 Include new sites
Measure Change
0
1
2
3
4
Structures
Guidelines
Forms
Data mgmt
Decision-
making
Links to Nat'l
system
Follow-up
Baseline
0
1
2
3
4
Structures
Guidelines
Forms
Data mgmt
Decision-
making
Links to Nat'l
system
Follow-up
Baseline
Measure Change
0
1
2
3
4
Structures
Guidelines
Forms
Data mgmt
Decision-making
Links to Nat'l
system
Follow-up
Baseline
Results
 Measurable
improvements in M&E
plans, performance and
data quality
 Partners budgeting for
M&E and hiring staff,
providing supportive
supervision, building
capacity, conducting
internal DQA
Asante sana!
Concluding Thoughts
 Adapt for local use
 Adaptions should be
careful documented
 RDQA should be
institutionalized within the
local organization
 Use “actionable findings”
www.measureevaluation.org/eop

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Adapting Data Quality Assurance Approaches and Tools to Meet Local Needs