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Adapting Data Quality Assurance
Approaches and Tools
to Meet Local Needs
Stephanie Mullen
MEASURE Evaluation
End-of-Phase-...
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,
MEASU...
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...
Data Quality Assurance Approach
Objective
Routine Monitoring
(all health programs)
Sampling
Purposive
Data Collectors
 He...
Deliverables
DataQuality
StandardOperating
Procedures(SOP)
Routine Data
Quality
Assessment
(RDQA) SOP
Botswana-RDQA
Tool
(...
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 Offic...
Evidence of Success
Adapting Data Quality Assurance
Approaches and Tools to Meet
Local Needs in Tanzania
Karen Foreit, Mari Hickmann, Zaddy Ki...
MEASURE Evaluation in Tanzania
Strengthen M&E
systems and capacity
 Improve data quality
 Enhance individual and
organiz...
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 a...
New Data Collection Instrument
Community Trace
and Verify
 Visit “claimed”
beneficiaries
 Ask what services
they receive...
No more “M&E 101”!
Tailored Capacity-building
 Prioritize problems
identified by DQA
 Group participants with
common pro...
Empiricalevidenceof
projectsuccessand/or
continuingchallenges
Measure Change
 Repeat DQA
 Focus on areas
selected for
ca...
Measure Change
0
1
2
3
4
Structures
Guidelines
Forms
Data mgmt
Decision-
making
Links to Nat'l
system
Follow-up
Baseline
0...
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...
Asante sana!
Concluding Thoughts
 Adapt for local use
 Adaptions should be
careful documented
 RDQA should be
institutionalized with...
www.measureevaluation.org/eop
Adapting Data Quality Assurance Approaches and Tools to Meet Local Needs
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Adapting Data Quality Assurance Approaches and Tools to Meet Local Needs

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Presented by Stephanie Mullen, Suzanne Cloutier and Karen Foreit at the MEASURE Evaluation End-of-Phase-III Event.

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Transcript of "Adapting Data Quality Assurance Approaches and Tools to Meet Local Needs "

  1. 1. Adapting Data Quality Assurance Approaches and Tools to Meet Local Needs Stephanie Mullen MEASURE Evaluation End-of-Phase-III Event, May 22, 2014
  2. 2. Why Do We Care About Data Quality? UNAIDS “Organizing Framework for a Functional National HIV M&E System”
  3. 3. 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. 4. 4 Additional Data Quality Tools  Multi-Indicator RDQA Tool  Longitudinal RDQA Tool
  5. 5. Applications of DQA/RDQA
  6. 6.  Botswana  Suzanne Cloutier  Tanzania  Karen Foreit Country Experiences
  7. 7. 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
  8. 8. 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
  9. 9. Deliverables DataQuality StandardOperating Procedures(SOP) Routine Data Quality Assessment (RDQA) SOP Botswana-RDQA Tool (B-RDQATool) B-RDQATool User Manual Data Quality Training Curriculum
  10. 10. B-RDQA Tool Consultative Workshop April 2012
  11. 11. SOP Consultative Workshops June 2012
  12. 12. Data Quality Training Workshops Nov 2012 Apr 2013
  13. 13. Sharing Our Process Global Maternal Health Conference 2013 American Public Health Association Annual Meeting 2013
  14. 14. Keys To Success MoH Champion Country Ownership Decentralization
  15. 15. 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
  16. 16. Evidence of Success
  17. 17. 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
  18. 18. MEASURE Evaluation in Tanzania Strengthen M&E systems and capacity  Improve data quality  Enhance individual and organizational capacity  Promote data for decision making
  19. 19. DQA for M&E Capacity-building  New sampling procedures  New instruments  Tailored training  Measure change
  20. 20.  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
  21. 21. New Data Collection Instrument Community Trace and Verify  Visit “claimed” beneficiaries  Ask what services they received  Compare answers to activity reports
  22. 22. No more “M&E 101”! Tailored Capacity-building  Prioritize problems identified by DQA  Group participants with common problems  Follow group training with individualized mentoring
  23. 23. Empiricalevidenceof projectsuccessand/or continuingchallenges Measure Change  Repeat DQA  Focus on areas selected for capacity-building  Include new sites
  24. 24. 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
  25. 25. Measure Change 0 1 2 3 4 Structures Guidelines Forms Data mgmt Decision-making Links to Nat'l system Follow-up Baseline
  26. 26. 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
  27. 27. Asante sana!
  28. 28. Concluding Thoughts  Adapt for local use  Adaptions should be careful documented  RDQA should be institutionalized within the local organization  Use “actionable findings”
  29. 29. www.measureevaluation.org/eop

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