270233 Color-blind and classless: The bias problems with health risk appraisals

Monday, October 29, 2012

Joseph Sudano, PhD , Center for Health Care Research and Policy, Case Western Reserve University at the MetroHealth System, Cleveland, OH
Adam Perzynski, PhD , Center for Healthcare Research and Policy, Case Western Reserve University at The MetroHealth System, Cleveland, OH
Steven Lewis, MS , Center for Healthcare Research and Policy, Case Western Reserve University at The MetroHealth System, Cleveland, OH
U.S. racial/ethnic health disparities have been documented over the past decades, yet disparities persist despite national/regional efforts to improve care access and quality. Health risk appraisals (HRA) can be important tools in assessing the impact of risk factors 1) potentially under the control of the individual, and 2) that may be amenable to social, public health, medical or pharmacological interventions. HRA's can provide patients with specific information about their health risks, what they can do about them, and give healthcare providers a tool to improve communication with patients regarding health, risks and prevention issues. Conspicuously missing from all or nearly all HRA's available today is any use of race/ethnicity or socioeconomic status (SES) in the actual risk calculation engines. One design group commented that attempts to create a better fit by creating race-specific values for use in the risk engines generated unreasonably different estimates for males of different races with otherwise identical characteristics. This suggests that current risk algorithms in most HRA's 1) lack statistical precision and validity across racial/ethnic groups and SES, 2) under-estimate the risk levels for African Americans, and 3) fail to transparently identify health disparities. As an example, we have documented these statements by empirically verifying the exclusion of race/ethnicity in risk calculations in HRA's used by the CDC, Marine Corp, Healthier People Network, Dr. Oz's Real Age and several others. We suggest possible solutions to this bias that include a rigorous review and incorporation of evidence-based research on risks related to race/ethnicity/SES and inclusion of personalized genetic information in HRA's.

Learning Areas:
Administer health education strategies, interventions and programs
Communication and informatics
Planning of health education strategies, interventions, and programs

Learning Objectives:
Describe how health risk assessment tools calculate risk. Discuss the problems associated with using race and socioeconomic status in risk engines in health risk assessment tools.

Keywords: Health Disparities, Health Risks

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have a large grant that will design a new health risk assessment tool and I have several years of experience in this area of research.
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.