Online Program

292579
Health disparities megacommunity: Creating a model to address the rising demand and cost of healthcare amongst baby boomers


Wednesday, November 6, 2013 : 9:10 a.m. - 9:30 a.m.

Kimberly Baldwin, MS, Booz Allen Hamilton, Rockville, MD
Ricky Brathwaite, PhD, MS, MSHS, Healthcare, Atlas Research LLC, Washington, DC
Kenneth Wiley Jr., PhD, Booz Allen Hamilton, Rockville, MD
Anthony Barbagallo, Booz Allen Hamilton, Atlanta, GA
Shileah Cantey, MSW, Booz Allen Hamilton, Atlanta, GA
Samuel Perry, Booz Allen Hamilton, Atlanta, GA
Reducing minority health disparities (HD) would have saved $1.24 trillion between 2003 and 2006 including nearly $230 billion in direct medical care costs. Researchers have determined that HDs follow geographic lines. Geographic isolation, socio-economic status, health risk behaviors, and limited job opportunities contribute to HDs in rural communities. While 20% of the United States population lives in rural areas, higher rates of chronic illnesses and poor overall health are found in these communities. Also, AARP has detected migration patterns of baby boomers from urban to rural areas which has the potential to overwhelm the rural infrastructure where there are fewer resources to meet the demand for health care. To confront this ongoing issue, we developed a reproducible and transferrable Health Disparities Solutions Model (HDSM). Such a model will use analytics and information technology to align resources of potential stakeholders to address the inequities in a given geographical area. Our HDSM will allow a user to input a HD issue (i.e., access to care) and obtain a picture of how a selected geographic location's resources can be used to address the defined problem. When the model is run, the cross-walk of these variables output a structured report that identifies specific local entities with resources that can be utilized to reduce the HD within a targeted area. These entities could be traditional (e.g., hospital) or non-traditional (e.g., Wal-Mart). We can leverage predictive analytics within HDSM to identify stakeholders in non-local areas and create a roadmap that regional stakeholders can follow as they develop stakeholder networks and establish Megacommunities around HD-specific issues. HDSM will identify resource gaps using computation analysis. This will allow local leaders to consider efficient policies that can assist in reducing the various resource gaps that prevent improvement of health in their communities.

Learning Areas:

Assessment of individual and community needs for health education
Biostatistics, economics
Diversity and culture
Systems thinking models (conceptual and theoretical models), applications related to public health

Learning Objectives:
Explain how our Health Disparities Solution Model (HDSM) will allow a user to input a HD issue (i.e., access to care) and obtain a picture of how a selected geographic location’s resources can be used to address the defined problem. Describe how the HDSM will help identify resource gaps using computation analysis. Explain how leveraging a Megacommunity to vet the model will allow local leaders to consider efficient policies that can help to fill the resource gaps for the betterment of health in their communities.

Keyword(s): Cost-Effectiveness, Health Disparities

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have been a co-principal of multiple federally funded grants focused on various health disparities topics, such as obesity and rural health. I have created models and mobile apps to support health disparities endeavors and increase technology awareness
Any relevant financial relationships? Yes

Name of Organization Clinical/Research Area Type of relationship
Booz Allen Hamilton Health Disparities Consultant

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.