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Updated: Jun 3, 2026

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials
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Published on: April 19, 2024

Sensitivity analysis in cost-effectiveness studies: from guidelines to practice.

Rahul Jain1, Michael Grabner, Eberechukwu Onukwugha

  • 1Department of Clinical and Administrative Pharmacy, College of Pharmacy, University of Georgia, Athens, Georgia, USA.

Pharmacoeconomics
|March 15, 2011
PubMed
Summary
This summary is machine-generated.

Cost-effectiveness analysis (CEA) relies on assumptions, creating uncertainty. Sensitivity analysis (SA) evaluates this, but current practices often neglect key uncertainty sources, necessitating improved SA guidelines and reporting for better health technology assessment.

Related Experiment Videos

Last Updated: Jun 3, 2026

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials
08:36

The Adjuvant Efficacy of Angong Niuhuang Pill in the Treatment of Viral Encephalitis: A Meta-Analysis of Randomized Controlled Trials

Published on: April 19, 2024

Area of Science:

  • Health economics
  • Decision science
  • Health technology assessment

Background:

  • Cost-effectiveness analysis (CEA) is crucial for economic evaluations in healthcare.
  • Uncertainty in CEA assumptions can impact findings, necessitating robust sensitivity analysis (SA).
  • Existing reviews highlight a gap between SA guidelines and actual research practice, with limited attention to all uncertainty sources.

Purpose of the Study:

  • To consolidate all sources of uncertainty in CEA.
  • To assess the attention given to SA across different uncertainty sources.
  • To provide criteria for conducting and reporting SA to improve practice and bridge the gap between guidelines and implementation.

Main Methods:

  • Comprehensive review of uncertainty sources in CEA (parameter, structural, methodological, patient heterogeneity).
  • Literature review of SA conduct and reporting in 406 CEA articles (2000-2009).
  • Analysis stratified by common modeling approaches (decision analysis, regression models).

Main Results:

  • A minority of studies addressed multiple uncertainty sources, with no improvement over time.
  • The use of advanced techniques like probabilistic SA has increased significantly.
  • Significant disparities exist in the attention paid to different SA sources.

Conclusions:

  • Researchers should adopt a more comprehensive approach to SA in economic evaluations.
  • Clearer criteria for conducting and reporting SA are needed to enhance the quality and utility of CEA.
  • Improved SA reporting is essential for informed decision-making in health technology assessment.