dr m bhattacharya
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- 1. Data Triangulation in HIV
Prof Madhulekha Bhattacharya
HOD ,Deptt of Community Health Administration
National Institute of Health & Family Welfare
Munirka,New Delhi--67
2. Data Triangulation
Is an analytical approach that integrates multiple data sources to
improve understanding of a public health problem and to guide
programmatic decision-making to address these problems
Involves the synthesis and integration of data from multiple
sources through collection, examination, comparison and
interpretation
By collecting and comparing multiple data sets with each other,
triangulation helps to overcome biases inherent in each data
source
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3. Gather data from multiple sources
Refine hypothesis (corroborate, refute or modify)
Examine data
Planning Triangulation
Conducting Triangulation
Communicating Results (for Action)
A visual representation of the triangulation process
4. Differencefrom ---
Meta Analysis
Data triangulation
Meta analysis combines rigourous scientificdata of similar quality
and design toconduct statistical analysis
Uses data from diverse sources
Lists judgements and limitations of each
To be used by programme managers policy makers , and also
researchers
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5. Steps in Data Triangulation
Specify the question
Identify data sources, organize the data and identify data
gaps
Conduct data quality and validation checks
Decide on data outlier and/or missing data
Refine/revisit the questions chosen for data triangulation
Analyze data from different sources for each question
Data triangulation
Summarize findings and draw conclusions
Outline next steps based on findings
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6. Questions
What are the levels, differentials and trends in HIV/STI in general
population, high-risk groups, and the bridge population?
What are the drivers of the epidemic?
What are the gaps in HIV/AIDS response at district level?
What are the data gaps?
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7. Identifying and refining key questions
Brainstorming questions
Refining brainstormed questions
Key question(s)
- Data available
8. Important, answerable 9. Actionable, appropriate 10. Method
appropriate 11. Feasiblebhattacrya-NIHFW
12. Data sources
1. Data from HIV Sentinel Surveillance for different population
groups
2. ICTC/PPTCT data on HIV prevalence
3. Mapping of HRGs - urban (under TI program) & rural (under
Link Worker Program)
4. ART registration data
5. Behavioural Sentinel Survey (BSS)
6. Integrated Biological & Behavioural Assessment (IBBA)
7. Blood Bank data, STD Clinic data
8. Census of India, NFHS-3, DLHS-3
9.Any special studies
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NATIONAL INSTITUTE OF HEALTH & FAMILY WELFARE MUNIRKA, NEW
DELHI 110067.
13. Inputs to Evidence-Based Planning
Overall burden of HIV
Sub-population distribution of HIV
Basic HIV transmission dynamics
Assessing gaps in responses to HIV situation
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- Evidence required at the lowest levels of planning such as Districts and Sub-districts
14. Integration and triangulation using data from different sources 15. To Use valid and standardized methods to ensure that evidence derived is credible and comparable across states and districts
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