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Racial and Ethnic Disparities and Perceptions of Health Care: Does Health Plan Type Matter?

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This study examined whether racial and ethnic minorities' higher levels of dissatisfaction with and distrust of their physicians (a well-documented phenomenon) could be explained by the type of restrictive, highly managed health plans in which racial and ethnic minorities are more likely to be enrolled. Other studies on this topic have reported racial and ethnic disparities in trust and satisfaction, compared to Caucasians, while not controlling for health plan restrictiveness. Trust and satisfaction issues have also been linked to health outcomes. Data were collected by telephone surveys, (available in Spanish if necessary), of adults nationwide, using the 1998–1999 Community Tracking Household and Followback Studies. The final regression analysis was performed on 32,830 respondents. The model addressed predisposing factors (age, gender education), enabling factors (poverty, demographic information such as county residence) need factors (health status) and medical care factors (i.e., utilization of health care, unmet needs).

Respondents were asked to rate four statements about their physicians on a scale of 1–5, from "strongly agree" to "strongly disagree." Three questions about care received on the last office visit were asked and five answers were available, ranging from poor to excellent. Levels of trust and satisfaction varied considerably by race, particularly trust, even after controlling for predisposing, enabling, need and medical factors. Enrollment in tightly managed HMO plans was significantly associated with lower levels of trust and satisfaction. For all populations, health plan type is not a confounding factor and does not explain differences in trust and satisfaction that show up in racial and ethnic minorities. Limitations of the study include communication barriers encountered during interviews; the fact that measurement of trust is an inexact science; lack of data on physician-patient race concordance; and missing data from nonresponsive interviewees that may have skewed analysis.