Conceptualizing race in economic models of medical utilization: a case study of community-based elders and the emergency room

There is no consensus on the appropriate conceptualization of race in economic models of health care. This is because race is rarely the primary focus for analysis of the market. This article presents an alternative framework for conceptualizing race in health economic models. A case study is analyz...

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Bibliographic Details
Published in:Health services research 1995-04, Vol.30 (1 Pt 2), p.207-223
Main Author: White-Means, S I
Format: Article
Language:English
Subjects:
Activities of daily living
African Americans - statistics & numerical data
Aged
Case studies
Continental Population Groups
Culture
Demographic aspects
Economic aspects
Economic models
Education
Emergency medical care
Emergency Service, Hospital - economics
Emergency Service, Hospital - statistics & numerical data
Emergency Service, Hospital - utilization
European Continental Ancestry Group - statistics & numerical data
Expenditures
Family income
Female
Health care delivery
Health insurance
Health Services Needs and Demand - economics
Health Services Needs and Demand - statistics & numerical data
Home Care Services - economics
Home Care Services - statistics & numerical data
Home Care Services - utilization
Humans
Labor economics
Labor market
Long term health care
Male
Medical care
Medical care (Private)
Models, Economic
Race
Socioeconomic Factors
Statistical analysis
Studies
United States
Utilization review
Variables
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Summary:There is no consensus on the appropriate conceptualization of race in economic models of health care. This is because race is rarely the primary focus for analysis of the market. This article presents an alternative framework for conceptualizing race in health economic models. A case study is analyzed to illustrate the value of the alternative conceptualization. The case study findings clearly document the importance of model stratification according to race. Moreover, the findings indicate that empirical results are improved when medical utilization models are refined in a way that reflects the unique experiences of the population that is studied.
ISSN:0017-9124
1475-6773