Analytics: Unpacking AIDS Policy in the Black Community

Analytics: Unpacking AIDS Policy in the Black Community

Fay Cobb Payton (North Carolina State University, USA)
Copyright: © 2008 |Pages: 7
DOI: 10.4018/978-1-59904-889-5.ch008
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Abstract

Business analytics (BA), often termed business intelligence (BI), applications can carefully provide insight into the (in)significance of these factors in healthcare system’s ability to treat AIDS/HIV, in general. In particular, demographic variables that relate to cultural, socioeconomic status and community dimensions of those most impacted (namely Black Americans in the United States which is the focus of this writing) by the AIDS/HIV epidemic are often disregarded. For the broader community, the questions to address are diverse. What can business analytics inform us about Black Americans infected by AIDS/HIV? What are the broader cultural issues that are not often modeled by analytical tools? How do these findings stand to impact public policy and how the healthcare community can better assist those living with the disease? In this chapter, I take on these questions by first reviewing major issues and trends in AIDS/HIV and IT literatures by focusing on health disparities in one historically underserved group, namely Black Americans. Next, I present public health conceptual framework that augments this discourse by depicting those factors uncovered in traditional information technology/systems works. This paper concludes with recommendations for future research opportunities for examining AIDS/HIV public policy issues.

Key Terms in this Chapter

ICD-9 Codes: International Classification of Diseases–9th Division

Vulnerability: Propensity of poor health and/or lack of access to health care services.

Business Analytics/Intelligence: Use of data and information to drive business actions, including concepts of performance management, definition and delivery of business metrics, data visualization by using online analytical processing (OLAP), dashboards, scorecards, analytic applications, and data mining.

Managed Care: An arrangement of specific health providers that are contracted through a structured plan for managing service delivery and cost of care.

Healthy People 2010: Objectives for the United States to achieve specified health care status, based on a 10-year timeframe. These objectives include extensive discussion on vulnerable populations, community groups, providers, and so forth, in an effort to improve overall health.

Cultural Competency: The ability of an organization, group, or individual to work crossculturally in an effort to administer health care services and treatment; this is critical to the patient-physician relationship along with access to appropriate care and quality outcomes.

Health Disparities: Differences in the incidence, prevalence, mortality, burden of disease, or other adverse health conditions that exist among specific population groups.

Diagnostic Related Groups (DRGs): A classification of hospital case types into groups expected to have similar hospital resource use. The groupings are based on diagnoses (using ICD), procedures, age, sex, and other attributes.

Capitation: Typically associated with managed care; a fixed payment or reimbursement plan that physicians receive based on care delivery to patients.

Socioeconomic Status (SES): A measure of social and economic position that is a function of occupation, income level, and education.

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