Introduction to Basic Data Analysis and Interpretation for Health Programs

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Introduction to Basic Data Analysis and
Interpretation for Health Programs
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Training Objectives

• To improve understanding of statistical and
  monitoring and evaluation (ME) 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

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Training Overview

• Training introduction
• Module 1 Data analysis key concepts
• Module 2 Basic analyses
• Module 3 Data presentation interpretation
• Review of key themes

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Introductions
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Training Introduction
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Training Introduction Learning Objectives

• Understand the importance of improving
  data-informed decision making
• Understand the role of monitoring and evaluation
  (ME) data in decision making
• Understand the importance of data analysis and
  interpretation

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• 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

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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

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Context
Pressing need to develop health policies,
strategies, and interventions
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Monitoring and Evaluation

• Track changes in program performance over time
• Monitoring
• Attribute program outcomes to their causes
• Evaluation

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Data

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

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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

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ME Is Not an Enemy

• Policymakers, program managers, and ME/strategic
  information specialists can be partners
• Strong decision making and management rely on
  high-quality ME / strategic information
• Data quality is linked to data use

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Monitoring and Evaluation allows.

• data-based decisions,
• which lead to
• better health programs and
• better health outcomes

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Group Participation

• Who analyzes and interprets data in your
  organization?

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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

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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

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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

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Key Messages

• Decisions based on evidence lead to better health
  outcomes
• We all have a role in ME partners in progress
• High-quality information is needed for decision
  making at policy, planning, and program levels
• Purpose of ME is not just to produce more
  information but to inform action