269987 A method to address community effect modification and avoid bias in evaluating mammogram interventions

Tuesday, October 30, 2012 : 9:30 AM - 9:50 AM

Vincent Agboto, MS, PhD , Family and Community Medicine, Meharry Medical College, Nashville, TN
Robert Levine, MD , Department of Family & Community Medicine, Meharry Medical College, Nashville, TN
Maureen Sanderson, MPH, PhD , Family and Community Medicine, Meharry Medical College, Nashville, TN
Barbara Kilbourne, PhD , Department of Family & Community Medicine, Meharry Medical College, Nashville, TN
Tan Ding, MS , Family and Community Medicine, Meharry Medical College, Nashville, TN
BACKGROUND: Even though it is known that biologically identical community-based public health interventions may have significantly different outcomes because of contextual factors, Cochran reviewers note that community-based public health intervention research rarely accounts for effect modification by place.

METHODS: We first define a health disparity function D: I → R2, where I is a set of communities identifiers and R2 is the set of vectors of dimension. We then use a mathematical relation to create a classification scheme among communities based on the disparity function and prior experience. As an exemplar, we use data for regular screening mammography (≥ 1 per two years for women 65-74 years) following Medicare's 1991 decision to reimburse providers for screening mammography. Two county-based cohorts of 1,000,000 non-Hispanic women, each of whom were alive from 1992-95 (T1) or 2005-08 (T2), were obtained from all Medicare beneficiaries using complex probability sampling to enrich Black inclusion. Screening mammography was identified with an adapted Smith-Bondman algorithm.

RESULTS: Probability distributions are computed for each community set. Probability based stratified random sampling yields community sets across the spectrum of community-level outcomes which are significantly different from those which might be obtained through haphazard selection, selection based on co-location of an academic medical center, or selection based on socio-demographic characteristics.

CONCLUSIONS: The new methodology is theoretically advantageous as it makes no assumptions about community capability and achieves a greater likelihood of selecting communities that comprise the full spectrum of community contextual issues.

Learning Areas:
Biostatistics, economics
Epidemiology
Implementation of health education strategies, interventions and programs
Public health or related research

Learning Objectives:
Formulate a statistical based design method to address effect modification and avoid bias in evaluating mammogram interventions

Keywords: Statistics, Mammography Screening

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have been a co-author of multiple papers focusing on epidemiology and research methodology. Among my methodological interests are problems with internal and external validity for evaluating interventions. This paper addresses these issues. Moreover, I have taught multivariate analysis at the PhD level at Vanderbilt University for ten years and served as the consultant for biostatistics on multiple federally funded grants.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.