Natural Experiments: An Overview of Methods, Approaches, and Contributions to Public Health Intervention Research

Annu Rev Public Health. 2017 Mar 20:38:39-56. doi: 10.1146/annurev-publhealth-031816-044327. Epub 2017 Jan 11.

Abstract

Population health interventions are essential to reduce health inequalities and tackle other public health priorities, but they are not always amenable to experimental manipulation. Natural experiment (NE) approaches are attracting growing interest as a way of providing evidence in such circumstances. One key challenge in evaluating NEs is selective exposure to the intervention. Studies should be based on a clear theoretical understanding of the processes that determine exposure. Even if the observed effects are large and rapidly follow implementation, confidence in attributing these effects to the intervention can be improved by carefully considering alternative explanations. Causal inference can be strengthened by including additional design features alongside the principal method of effect estimation. NE studies often rely on existing (including routinely collected) data. Investment in such data sources and the infrastructure for linking exposure and outcome data is essential if the potential for such studies to inform decision making is to be realized.

Keywords: causal inference; evaluation methods; population health interventions.

Publication types

  • Review

MeSH terms

  • Decision Making
  • Health Priorities
  • Healthcare Disparities*
  • Humans
  • Public Health*
  • Research*
  • Socioeconomic Factors