Presentation

1. INTRODUCTION TO BASIC DATA
ANALYSIS AND INTERPRETATION
FOR HEALTH PROGRAMS

2. Training Objectives
 To improve understanding of statistical and
monitoring and evaluation (M&E) concepts in data
analysis
 To build skills in basic data analysis, including
setting targets and calculating program coverage,
and service utilization and retention
 To enhance skills in data interpretation

3. Training Overview
 Training introduction
 Module 1: Data analysis key concepts
 Module 2: Basic analyses
 Module 3: Data presentation &
interpretation
 Review of key themes

4. Introductions

5. Training Introduction

6. Training Introduction: Learning
Objectives
 Understand the importance of improving
data-informed decision making
 Understand the role of monitoring and
evaluation (M&E) data in decision making
 Understand the importance of data
analysis and interpretation

7. “… without information, things are done arbitrarily
and one becomes unsure of whether a policy or
program will fail or succeed. If we allow our
policies to be guided by empirical facts and data,
there will be a noticeable change in the impact of
what we do.”
National-level Policymaker, Nigeria

8. Why Improve Data-informed
Decision Making?
 HIV epidemic
 Resurgence of TB
 Continued prevalence of malaria
 Pockets of stalled fertility decline
 Population burden
 Shortage of health care workers

9. Context
Pressing need to develop health
policies, strategies, and
interventions

10. Monitoring and Evaluation
 Track changes in program performance over
time
Monitoring
 Attribute program outcomes to their causes
Evaluation

11. Data
 Data sources
 Service delivery statistics
 Census
 Surveys, evaluations, research studies
 Sentinel surveillance
 Budget information
 Data vs. information =
unsynthesized vs. synthesized

12. Purposes of Monitoring and
Evaluation
 Determine whether a plan or program is on
schedule with planned activities
 Assess whether a policy, plan, or program
has produced desired impacts
 Generate knowledge:
• Identify programmatic gaps, factors that influence
health outcomes, etc.
 Inform policy, planning, or program decisions

13. M&E Is Not an Enemy
 Policymakers, program managers, and
M&E/strategic information specialists can be
partners
 Strong decision making and management
rely on high-quality M&E / strategic
information
 Data quality is linked to data use

14. data-based decisions,
which lead to…
better health programs and
better health outcomes
Monitoring and Evaluation
allows….

15. Group Participation
Who analyzes and
interprets data in your
organization?

16. We can use information to…
 Inform policies and plans
 Raise additional resources
 Strengthen programs and improve results
 Ensure accountability and reporting
 Improve quality of services provided
 Contribute to global lessons learned

17. “Making Data Speak” in Thailand
 Need: Strengthen commitment of policymakers to
HIV prevention
 Data: Behavioral and epidemiological data
 Response:
 Analyzed data with Asian Epidemic Model and GOALS model
 Determined responses and resources needed
 Communicated data to stakeholders
 Decision/Action:
 Successfully emphasized prevention agenda in national strategic
plan and developed an operational plan to guide prevention
programming

18. Using NNRIMS Data to Inform
Resource Allocation
 Need: Strengthen monitoring of HIV/AIDS service
delivery
 Data: HIV service delivery indicators
 Response:
 Development of NNRIMS, a routine information system
 Quarterly reports summarizing data prepared for and
reviewed by LGA managers & decision makers
 Decision/Action:
 Chairman procured 480 HIV test kits, enabling more people
to get tested in Doma

19. Key Messages
 Decisions based on evidence lead to better
health outcomes
 We all have a role in M&E – partners in progress
 High-quality information is needed for decision
making at policy, planning, and program levels
 Purpose of M&E is not just to produce more
information but to inform action