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The “why” and the “how” of routine data collection: Real world examples of using data from routine HMISs in policy and programming

In this session from the Making Self-Injection Count workshop, presenters discussed challenges to data use for decision-making and shared examples of how countries and programs have made data actionable in other health areas, specifically Malaria and immunization. The presentation included an example of an application of routine family planning data, including a new analysis of self-injection data from Senegal, and wrapped up with a panel Q&A focused on solutions.


By the end of this session, participants were able to:

  • Understand key principles for fostering data use for decision-making.
  • Understand how countries and programs have used routine health data for decision-making.
  • Identify strategies to overcome challenges to data use.
  • Consider data quality and understand how it can be evaluated.

Key takeaways

  • Better data will lead to better decision-making and better health outcomes.
  • Data should:
    • be subjected to quality audits.
    • be delivered in a form that works for each intended audience and in alignment with their goals.
    • be shared with those who contributed the data and who have control over how services are offered.
    • include visualizations that effectively convey key details.
    • be iterative and ongoing.
  • There is a need for standardized metrics that allow for comparability among countries.


  • Jonathan Drummey, Data Visualization Specialist, PATH
  • Fred Njobvu, Technical Advisor, Center for Digital & Data Excellence, PATH
  • Marie-Reign Rutagwera, Strategic Information Advisor, PAMO Plus, PATH
  • Jessica Williamson, Data Analyst, Track20 Project, Avenir Health