医疗保健
医学
逻辑回归
卫生公平
家庭医学
民族
非洲裔美国人
老年学
公共卫生
护理部
政治学
民族学
历史
内科学
法学
作者
Kathleen Thiede Call,Donna McAlpine,Pamela Jo Johnson,Timothy J. Beebe,James A. McRae,Xue Song
出处
期刊:Medical Care
[Lippincott Williams & Wilkins]
日期:2006-05-17
卷期号:44 (6): 595-600
被引量:132
标识
DOI:10.1097/01.mlr.0000215901.37144.94
摘要
Objective: We sought to examine the extent to which reported barriers to health care services differ between American Indians (AIs) and non-Hispanic Whites (Whites). Methods: A statewide stratified random sample of Minnesota health care program enrollees was surveyed. Responses from AI and White adult enrollees (n = 1281) and parents of child enrollees (n = 572) were analyzed using logistic regression models that account for the complex sample design. Barriers examined include: financial, access, and cultural barriers, confidence/trust in providers, and discrimination. Results: Both AIs and Whites report barriers to health care access. However, a greater proportion of AIs report barriers in most categories. Among adults, AIs are more likely to report racial discrimination, cultural misunderstandings, family/work responsibilities, and transportation difficulties, whereas Whites are more likely to report being unable to see their preferred doctor. A higher proportion of adult enrollees compared with parents of child enrollees report barriers in most categories; however, differences between parents of AIs and White children are more substantial. In addition to racial discrimination and cultural misunderstandings, parents of AI children are more likely than parents of White enrollees to report limited clinic hours, lack of respect for religious beliefs, and mistrust of their child's provider as barriers. Conclusions: Although individuals have enrolled in health care programs and have access to care, barriers to using these services remain. Significant differences between AIs and Whites involve issues of trust, respect, and discrimination. Providers must address barriers experienced by AIs to improve accessibility, acceptability, and quality of care for AI health care consumers.
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