Using population-based routine data for evidence-based health policy decisions: lessons from three examples of setting and evaluating national health policy in Australia, the UK and the USA

J Public Health (Oxf). 2007 Dec;29(4):463-71. doi: 10.1093/pubmed/fdm065. Epub 2007 Oct 17.


Background: The desire for evidence-based health policy and practice is well established. Routine population-based health information systems play a fundamental role to inform policy decisions and to evaluate their effectiveness.

Methods: This paper presents three case studies of using population-based data in national health policy from three countries--USA (prescription drug safety), Australia (childhood immunization) and UK (hospital waiting times)--which were chosen to represent a diversity of health policy issues. The utilization of population-based databases and the social and political context in which the data were used are examined. Our goal was to summarize general lessons learned for policy decision-makers and other users and developers of population-based databases.

Results: Key lessons presented include: the importance of political will in initiating and sustaining data collection and analysis at a national level; the types of decision-making factors databases can address; and how the data were integrated into the decision-making process.

Conclusion: Population-based routine data provide an important piece of the mosaic of evidence for health policy decision makers. They can be used to assess the magnitude of the health problem, including which populations are most vulnerable; to develop policy goals; and to track and evaluate the effectiveness of health policy interventions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Australia
  • Data Collection*
  • Databases, Factual
  • Drug-Related Side Effects and Adverse Reactions
  • Evaluation Studies as Topic
  • Evidence-Based Medicine*
  • Health Policy*
  • Humans
  • Immunization Programs
  • Policy Making*
  • State Medicine
  • United Kingdom
  • United States
  • Waiting Lists