People

DATA TO POLICY

RESOURCES

Investments in data collection and health information systems in low and middle-income countries have greatly increased the data available to inform policymaking. But turning these data into actionable evidence requires organizational capacity for policy analysis. By strengthening staff capacity and systems that link data to policy, government health agencies can make better use of evidence to improve population health, address inequities, and set priorities in line with the evolving burden of disease.

The Data to Policy (D2P) program, developed by Vital Strategies and the U.S. Centers for Disease Control and Prevention, aims to bridge the data-policy gap through team-based training and mentoring of health policy professionals. D2P participants develop data-driven policy briefs and recommendations that respond to government health priorities. The program imparts analytical skills – including root cause analysis and health and economic impact assessments, as well as techniques for communicating with stakeholders using data.

After participating in the D2P program, participants will be able to:

  • Use data and evidence to analyze a health problem
  • Identify policy options that address the root causes of the problem
  • Use stakeholder analysis, health impact assessment and economic evaluation methods to assess the cost-effectiveness and feasibility of policy options
  • Persuasively communicate policy recommendations to stakeholders and decision-makers

At an organizational level, the program results in:

  • A suite of data-driven policy recommendations in priority areas
  • Government staff equipped with skills and a practical toolkit to conduct policy analysis
  • Strengthened systems for data and evidence use
  • Institutionalized training and capacity development through training of trainers

The D2P program has been delivered in collaboration with governments in 20 countries across Asia, Africa, and Latin America, and has supported the development of more than 170 data-driven policy recommendations

Investments in data collection and health information systems in low and middle-income countries have greatly increased the data available to inform policymaking. But turning these data into actionable evidence requires organizational capacity for policy analysis. By strengthening staff capacity and systems that link data to policy, government health agencies can make better use of evidence to improve population health, address inequities, and set priorities in line with the evolving burden of disease.

The Data to Policy (D2P) program, developed by Vital Strategies and the U.S. Centers for Disease Control and Prevention, aims to bridge the data-policy gap through team-based training and mentoring of health policy professionals. D2P participants develop data-driven policy briefs and recommendations that respond to government health priorities. The program imparts analytical skills – including root cause analysis and health and economic impact assessments, as well as techniques for communicating with stakeholders using data.

After participating in the D2P program, participants will be able to:
     • Use data and evidence to analyze a health problem
     • Identify policy options that address the root causes of the problem
     • Use stakeholder analysis, health impact assessment and economic evaluation methods to assess the cost-effectiveness and feasibility of policy options
     • Persuasively communicate policy recommendations to stakeholders and decision-makers

At an organizational level, the program results in:
     • A suite of data-driven policy recommendations in priority areas
     • Government staff equipped with skills and a practical toolkit to conduct policy analysis
     • Strengthened systems for data and evidence use
     • Institutionalized training and capacity development through training of trainers

The D2P program has been delivered in collaboration with governments in 15 countries across Asia, Africa, and Latin America, and has supported the development of more than 100 data-driven policy recommendations.