Cost-effectiveness analysis: A proposal of new reporting standards in statistical analysis

Heejung Bang, Hongwei Zhao

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


Cost-effectiveness analysis (CEA) is a method for evaluating the outcomes and costs of competing strategies designed to improve health, and has been applied to a variety of different scientific fields. Yet there are inherent complexities in cost estimation and CEA from statistical perspectives (e.g., skewness, bidimensionality, and censoring). The incremental cost-effectiveness ratio that represents the additional cost per unit of outcome gained by a new strategy has served as the most widely accepted methodology in the CEA. In this article, we call for expanded perspectives and reporting standards reflecting a more comprehensive analysis that can elucidate different aspects of available data. Specifically, we propose that mean-and median-based incremental cost-effectiveness ratios and average cost-effectiveness ratios be reported together, along with relevant summary and inferential statistics, as complementary measures for informed decision making.

Original languageEnglish (US)
Pages (from-to)443-460
Number of pages18
JournalJournal of Biopharmaceutical Statistics
Issue number2
StatePublished - Mar 4 2014


  • Average cost-effectiveness ratio (ACER)
  • Censoring
  • Cost-effectiveness plane
  • Incremental cost-effectiveness ratio (ICER)
  • Mean
  • Median

ASJC Scopus subject areas

  • Pharmacology (medical)
  • Pharmacology
  • Statistics and Probability
  • Medicine(all)


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