Observational Studies in Economic Evaluation

Daniel E. Polsky, M. Baiocchi

Research output: Chapter in Book/Report/Conference proceedingChapter


The goal of an economic evaluation of medical interventions is to provide actionable information for policy makers. However, the demand for causal evidence in medicine far exceeds the ability to practically control, finance, and/or conduct randomized studies. Observational data offer a sensible alternative source of data for developing evidence about the implications of different medical interventions. However, for studies using observational data to be considered as reliable sources for evidence of causal effects, great care is needed to design studies in a way that limits the number of alternative explanations for observed differences in outcomes between intervention and control. In this article we highlight a number of the techniques and tools used in high-quality observational studies. We will also discuss a few of the common pitfalls to be aware of.

Original languageEnglish (US)
Title of host publicationEncyclopedia of Health Economics
Number of pages10
ISBN (Electronic)9780123756787
ISBN (Print)9780123756794
StatePublished - Jan 1 2014
Externally publishedYes


  • Average treatment effect
  • Average treatment effect on the treated
  • Hidden bias
  • Individual level treatment effect
  • Instrumental variables
  • Matching
  • Neonatal intensive care unit
  • Observed selection bias
  • Potential outcome framework
  • Probability weighting
  • Propensity score
  • Regression discontinuity
  • Selection bias
  • Sensitivity analysis
  • Strongly ignorable treatment assignment

ASJC Scopus subject areas

  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)


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