Introduction to Data Analysis for Health Programs

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

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