Error processing SSI file

Division of General Internal Medicine

Department Home >

  • Base >
  • You are here
Division of General Internal Medicine

Short Courses: Seminar in Health Services Research Methods: Economic Assessment in Randomized Trials

Academy Health
Tuesday, June 27, 2006

Course Description:

Prospective economic evaluation of clinical trials is an increasingly important component of the clinical development program for new clinical therapies (e.g., treatments, behavioral interventions, and drugs). The statistical methods used for analysis of economic data from prospective studies are constantly evolving. In this course, the faculty and participants will explore issues in the design and analysis of economic assessments in trials and introduce both standard and recently proposed statistical methods for these assessments. The course format is primarily didactic; its content is both theoretical and applied (with STATA 8.0 computer software documented to assist in use) and specifically addresses the following issues:

This workshop will explore issues in the design and analysis of patient-level cost data in randomized trials. The faculty will:

  1. discuss the steps and strategic issues in the design of economic assessments in prospective trials;

  2. illustrate the issues related to choice of univariate and multivariate methods (OLS, log OLS, GLM, etc.) for evaluating and reporting the impact of the intervention on costs; and

  3. introduce the different methods available for calculating and reporting sampling uncertainty (i.e. confidence intervals) for the joint comparison of costs and effects.

The workshop will be practical in orientation and will routinely provide examples to illustrate the "how tos." Sample datasets, program codes, and software will be provided. Participants are encouraged to bring laptops if they desire to run programs concurrently with the demonstrations by faculty.

Level and prerequisite: Intermediate.  The course has no prerequisite, but familiarity with economics and statistics will be helpful.