Session: Statistical and Modeling Techniques for Health Outcomes Research


Back to Annual Meeting Page		American Public Health Association 133rd Annual Meeting & Exposition December 10-14, 2005 Philadelphia, PA

3059.0: Monday, December 12, 2005: 8:30 AM-10:00 AM

Oral

Statistical and Modeling Techniques for Health Outcomes Research

Health outcomes research involves the collection and analysis of data that serves to provide evidence demonstrating the quality of medical care and public health programs. The assessment of patient-reported outcomes in clinical and health survey research has increased dramatically over the past several decades. Evaluations of symptoms, health status, quality of life and patient satisfaction are now primary and secondary outcomes in many clinical trials and observational studies. As indices and markers of therapeutic benefit and risk, these measures must be sensitive to differences that fall within a patient's operative range. Health care providers who must often prioritize resources across their members and among different conditions require a definitive metric. These evaluations typically use scales that have been developed to compare and contrast functioning relative to a given performance standard. To comprehensively evaluate the effectiveness of preventative programs and therapeutic interventions, investigators need to measure patient outcomes with the precision and accuracy that will allow for the detection of health improvements and health decrements that are important to the patient. The purpose of this session is to explore the various statistical, measurement and modeling techniques which can be used to evaluate the effectiveness of therapeutic interventions and prevention programs.

Learning Objectives: At the end of this session the participant should be able to: 1. Describe the main advantages of hierarchical models and identify potential areas of their application 2. Understand how quality initiatives may be applied to various health care settings 3. Articulate the advantages of using innovative computer adaptive technology (CAT) and item response theory (IRT) in health outcome assessments 4. Describe the growing importance of statistics in economic evaluation of health care

Presider(s):

Janet T. Eyster, PhD

8:30 AM

Using hierarchical models for the identification of factors associated with best practices and hospital profiling: Application to California birth data

Moshe Fridman, PhD, Lisa M. Korst, MD, PhD, Kimberly D. Gregory, MD, MPH

8:50 AM

Statistical Methods for Quality Initiatives

Brian E. O'Donnell, PhD, Kathleen Schneider, PhD, Debbie Dean, MS

9:10 AM

In Search of Power and Significance 10 Years Later
Jeffrey S. Hoch, PhD

See individual abstracts for presenting author's disclosure statement and author's information.

Organized by:

Statistics

Endorsed by:

Community Health Planning and Policy Development; Epidemiology; Maternal and Child Health; Mental Health; Occupational Health and Safety

CE Credits:

CME, Health Education (CHES), Nursing

The 133rd Annual Meeting & Exposition (December 10-14, 2005) of APHA