Clinical importance, statistical significance and the assessment of economic and quality-of-life outcomes

Health Econ. 1993 Oct;2(3):205-12. doi: 10.1002/hec.4730020303.


The assessment of economic and quality-of-life outcomes of health care interventions is moving into a new era, with such assessments increasingly being made within the context of controlled clinical trials. Traditionally the measurement of many variables in economic evaluations, particularly costs, has been deterministic. In the context of clinical trials the measurement of variables is stochastic, with the standard principles of statistical inference being applied to analyse differences between treatments in terms of effectiveness. Economists participating in clinical research are therefore being called upon to specify the sample size for the economic component of the evaluation and to undertake statistical tests for differences in cost or cost-effectiveness. This paper discusses the current methodological issues surrounding stochastic measurement in clinical trials, discusses the additional issues raised by the assessment of economic and quality-of-life outcomes and specifies the challenges facing economists if they are to answer the questions now being posed about economic analysis by statisticians and clinical researchers. It is concluded that application of the standard principles of statistical inference to economic data is not straightforward and will require value judgements to be made about statistical significance and economic importance, which may differ from those already made in purely clinical studies.

MeSH terms

  • Confidence Intervals
  • Cost-Benefit Analysis
  • Data Interpretation, Statistical*
  • Health Care Costs
  • Health Services Research / methods*
  • Humans
  • Outcome Assessment, Health Care* / statistics & numerical data
  • Quality of Life*
  • Randomized Controlled Trials as Topic*
  • Selection Bias
  • Sensitivity and Specificity
  • Stochastic Processes*
  • Treatment Outcome