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Health Inequality Monitoring Foundations: Health Data Disaggregation (WHO)

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About Course

Considerations related to health data disaggregation are present across the steps of health inequality monitoring, from selecting health indicators and dimensions of inequality to sourcing data, analyzing data, reporting results and developing evidence-informed approaches to promote health equity. An in-depth understanding of disaggregated health data and related issues is part of building and strengthening capacity for health inequality monitoring.

This course is an exploration of health data disaggregation, aiming to build both theoretical understanding and practical skills. Drawing on examples, the course begins by defining disaggregated data and demonstrating how they are relevant to health inequality monitoring. It closely examines the selection of health indicators and dimensions of inequality and considerations for measuring and categorizing dimensions of inequality. The course then addresses strategies and best practices for reporting disaggregated health data. The target audience is monitoring and evaluation officers, researchers and analysts, though the course is suitable for anyone with a general interest in health data and inequality monitoring.

This course is part of the Health Inequality Monitoring Foundations series, featuring the following courses: (1) Overview, (2) Data Sources, (3) Health Data Disaggregation, (4) Summary Measures of Health Inequality and (5) Reporting.

Course duration: Approximately 1.5 hours

Certificates: A Record of Achievement will be available to participants who score at least 80% of the total points available in the final assessment. Participants who receive a Record of Achievement can also download an Open Badge for this course. Click here to learn how.

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What Will You Learn?

  • How disaggregated health data are used across the steps of health inequality monitoring
  • Considerations for the selection of health indicators and dimensions of inequality
  • Approaches and considerations for measuring and categorizing dimensions of inequality
  • Characteristic patterns of inequality in disaggregated health data
  • Best practices for reporting disaggregated health data

Course Content

Module 0: Career Development

  • Career Assessment
    00:00

Module 1: Intro to Course

Module 2: Course Assessment

Module 3: Certification and Ranking

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