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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Ethn Dis. Author manuscript; available in PMC 2010 July 1.
Published in final edited form as:
Ethn Dis. 2009 Summer; 19(3): 330–337.
PMCID: PMC2750098
NIHMSID: NIHMS140919

The Association between Perceived Provider Discrimination, Health Care Utilization, and Health Status in Racial and Ethnic Minorities

Abstract

Background and Objectives

A commonly cited explanation of how racial discrimination impacts health is the biopsychosocial model. However, the biopsychosocial model does not allow for the effects of perceived provider discrimination on health behavior and utilization. In fact, researchers have directed relatively little attention towards the direct and indirect effects of perceived provider discrimination on both health care utilization and health status. We, therefore, compared the extent to which perceived provider discrimination explains racial/ethnic differences in health care utilization and subsequently health status.

Methods

The data came from the 2001 Survey on Disparities in Quality of Health Care. The final analytic sample was 5,642 adults living in the US. Structural equation modeling evaluated the relationship between perceived provider discrimination, health care utilization, and health status.

Results

African Americans, Hispanics, and Asians reported significantly more perceived provider discrimination and poorer health compared to non-Hispanic whites. Poor health is significantly mediated by two paths: (1) by perceived provider discrimination and (2) by perceived provider discrimination through unmet need for health care utilization.

Conclusions

Perceived provider discrimination contributes to health disparities in African Americans, Hispanics, and Asians. Perceived provider discrimination has a direct effect on self-reported health status. Additionally, because minorities perceive more provider discrimination, they are more likely to delay health seeking. In turn, this delay is associated with poor health. This enriches our understanding of how racial/ethnic health disparities are created and sustained and provides a concrete mechanism on how to reduce health disparities.

Keywords: Provider Discrimination, Health Status, Health Disparities, Utilization

Introduction

A focus of research on racial/ethnic disparities in health has been the relationship between racial discrimination across multiple dimensions, such as everyday discrimination, and poor physical and mental health outcomes.15 Specifically, perceiving or experiencing racial discrimination has been associated with giving birth to a low birth weight infant,1 having higher levels of elevated blood pressure,2 smoking,3 experiencing higher rates of depression,4 and consuming higher levels of alcohol.5

A commonly cited explanation of how racial discrimination impacts health is the biopsychosocial model. Under the biopsychosocial model, experiencing racial discrimination causes stress, which in turn, produces ill health, both physically and psychologically.68 Critiquing the biopsychosocial model, Bird and Bogart9 note, “despite its strengths, the biopsychosocial model does not take into account the direct effects of perceived discrimination in health care on health-related decisions and behaviors,”(p555) about which, less is known. It is posited9,10 that perceived provider discrimination will have a direct negative impact on health care utilization and health outcomes because individuals who perceive provider discrimination will have more dissatisfaction and less trust with that provider and with the overall health care system. These negative beliefs and experiences will, therefore, delay future health care utilization,9 and will have important health consequences which will continue to exacerbate racial/ethnic health disparities.10 However, this line of research remains largely unexplored,1113 leading researchers to conclude that “indentifying pathways between discrimination and health status and identifying ways to reduce experiences in health care settings that are perceived as discriminatory are 2 major tasks that remain for the field of health services research.”14(p913)

Therefore, it is our contention that perceived provider discrimination may contribute to health disparities through multiple pathways. Although the most commonly cited pathway is through the physiological and psychological stress produced from experiencing discrimination,68 other pathways exist, as previously posited,9,10 and researchers have directed relatively little attention toward these pathways. In fact, to our knowledge, no research has concurrently examined the direct and indirect effects of perceived provider discrimination on both health care utilization and health status. Studies have typically examined either the association between perceived provider discrimination and health care utilization10,12,13,1519 or the association between perceived provider discrimination and physical health status.14,20 For both of these lines of research, many have mixed findings, have an inability to generalize, and do not examine multiple racial/ethnic groups in detail. For example, Van Houtven et al.10 and Blanchard and Lurie15 found those who perceived health care discrimination were significantly more likely to delay health care utilization, while Casagrande et al.16 did not find an association between perceived health care discrimination and delay in getting medical care. Similarly, Piette et al.20 found that individuals who perceived health care discrimination had worse overall health, while Hausman et al.14 found that for Hispanics, perceived health care discrimination was not associated with worse overall health.

Beyond these mixed findings, the ability to generalize is another limitation with some findings of this line of research. For example, many studies focus on a single location in the US: Durham County, NC;10 two census tracts in Baltimore City, MD;16 or an AIDS organization in a Midwestern city.21 Another limitation is the tendency to examine primarily African Americans in discrimination research,1,2,4,9,14,16 which leaves out any ability to understand the importance and implication of discrimination felt by other racial/ethnic minorities. This understanding is important given the fast growing immigrant population and higher birth rates among racial/ethnic minorities in America. By 2025, it is estimated that racial/ethnic minorities will comprise 33 percent of the US population.22 “As such, the health of minority Americans is a critical component of the nation’s health.”22(p219)

Our study is unique in two ways. First, we advance the line of research linking perceived provider discrimination with racial/ethnic health disparities. We accomplish this by undertaking a structural equation model that examines perceived provider discrimination and the direct and indirect effects on health care utilization and health status. Second, we address two limitations found in previous research by including four racial/ethnic groups in our analysis and using a nationally representative sample.

Thus, the primary aim of our research is to explore different pathways that impact the health of racial and ethnic minorities. Based on findings from previous research, we test three related hypotheses:

  1. Perceived provider discrimination will have a positive direct effect on having an unmet need of health care utilization.
  2. Perceived provider discrimination will have both a positive direct and indirect effect on poor health status.
  3. Racial and ethnic minorities will perceive more provider discrimination, which will lead to having a poorer health status as compared to non-Hispanic whites.

Methods

Data

Our data come from the Survey on Disparities in Quality of Health Care, sponsored by the Commonwealth Fund (http://www.commonwealthfund.org). The data were collected using a random-digital-dialing telephone survey of adults aged 18 years and older in the continental U.S. in 2001 with African Americans, Hispanics, and Asians oversampled. Interviews were conducted in several languages based on respondents’ preferences. Data were weighted to adjust for disproportionate sampling and demographic distortion due to non-response. The full sample size was 6,722; however, to narrow a sample to the four representative racial/ethnic groups, the analytic sample is limited to non-Hispanic white, African American, Hispanic, and Asian respondents who used any health services within the last two years. The final analytic sample size for this study was 5,642.

Measures

Perceived provider discrimination, a latent variable, was measured through multiple questions. Respondents who had a health care visit in the last two years reported if they ever felt that the medical providers judged them unfairly or treated them with disrespect because of: a) racial/ethnic background; b) inability to pay for the care or the type of health insurance; c) language barrier; and d) gender. All of these variables were coded as 0=no and 1=yes. Although this paper is specifically about racial/ethnic minorities perceiving provider discrimination, we have chosen to also include perceived discrimination due to the inability to pay for care, language, and gender. Previous research has demonstrated that individual’s “perceptions of discrimination may be more global than some researchers may expect” because individuals experience the world holistically.20(p46) Thus, the distinction between perceived discrimination based on race, gender, and class may be meaningless for many individuals since they can experience all three at the same time.20

Unsatisfying interaction with a doctor, a latent variable, was measured through multiple author-selected questions. Respondents who had a health care visit in the last two years were asked if the provider: a) treated them with respect and dignity; b) involved them in decision making; and c) spent enough time with them. All of these questions were coded as 1=great deal to 4= not at all. Unmet need of health service utilization was assessed by a single question: “During the last 12 months, was there any time when you had a medical problem but put off, postponed or did not seek medical care when you needed it?” This variable was dichotomized into 0=no and 1=yes. Current poor health measured respondents’ self-reported health status and was coded from 1 = excellent to 5 = poor. Race/Ethnicity includes African American, Hispanic, and Asian. Non-Hispanic white is the reference group. In addition, control variables include gender, age, education, income, and type of health insurance.

Data Analysis

Structural equation modeling was estimated on covariance matrices using Mplus, which allows for a model with complex design and multiple imputations.23 A mixture of continuous, dichotomous, and ordinal indicators were used for structural equation modeling with latent variables.24 Although these data are cross-sectional, research can address inferring causation from correlation in cross sectional data.25 In our case, perceived provider discrimination and unsatisfied interaction with a doctor are experienced in the last two years, unmet need of health service utilization is within the last one year, while poor health status is a current measure, thus we can infer some causation based on a rationale and theoretical background.

Figure 1 shows the causal structure of the theoretical model. To evaluate the statistical significance of the models, the following tests of model fit are reported: the model chi-square and degrees of freedom (χ2); normed chi-square (χ2/df); comparative fix index (CFI); Tucker-Lewis index (TLI); the root mean square error of approximation (RMSEA). A significant χ2 (p<.05) indicates a poor fitting model, however the chi-square is sensitive to large (>200) sample sizes.25 This sensitivity is minimized using the normed chi-square (χ2/df). A model with a χ2/df ratio of 5.0 or less has an acceptable fit.26 Furthermore, models that have a CFI and TLI greater than .96 indicate a very good fitting model.27 Models that have an RMSEA less than .05 indicate a good fitting model.27

Figure 1
Theoretical model of provider discrimination, unsatisfying interaction with a doctor, and current poor health through unmet need of health service utilization.

Results

Table 1 presents the weighted percent of key variables in this study. Overall, 7.48% perceived provider discrimination due to inability to pay, 1.79% due to language, 2.92% due to race/ethnicity, and 3.31% due to gender. Almost one fifth (20.26%) of respondents reported having an unmet for health care utilization. For health status, the majority of respondents report their health as excellent (21.67%) or good (28.92%) with only 4.16% reporting poor health.

Table 1
Characteristics of respondents, N=5,642

Because perceived provider discrimination and unsatisfying interaction with a doctor were latent factors, we first estimated the confirmatory factor analytic model. The factor loadings ranged from .63 to .85 and were statistically significant (p < .001). The fit indices indicated a good fit of the confirmatory factor analytic model (χ2:23.721 with 13 df; χ2/df =1.825; CFI=.997; TLI=.995, RMSEA=.012). The correlation between two latent factors was moderate (.453) indicating that perceived provider discrimination and unsatisfying interaction with a doctor were separate factors

For our proposed theoretical model, we added explanatory variables (i.e. race/ethnicity), a mediating variable (i.e. unmet need for health care utilization), and an ultimate outcome variable (current poor health) (Figure 1). The combined model shows a very good model fit to the data (χ2:307.952 with 73 df; χ2/df = 4.22; CFI=.955; TLI=.919, RMSEA=.023). The standardized results of structure equation model are presented in Table 2. For a better understanding of the indirect effects, standardized linear regression coefficients for continuous outcomes (perceived provider discrimination, unsatisfying interaction with a doctor and current poor health status) and standardized probit regression coefficients for the dichotomous outcome (unmet need for health care utilization) are reported. Mplus correctly calculate indirect effects between standardized probit coefficients and standardized linear regression coefficients. In general, standard errors for standardized estimates are not reported in Mplus, which is typical when using the Maximum Likelihood method.26

Table 2
Parameter Estimatesa for the Structural Equation Model (N=5,642)

Impact of race and ethnicity on perceived provider discrimination & unsatisfying interaction with a doctor. When examining perceived provider discrimination, compared to non-Hispanic whites, African Americans, Hispanics, and Asians all report significantly more perceived provider discrimination. Compared to non-Hispanic whites, African Americans report the greatest perceived discrimination (B=0.118, p <.001). Race/ethnicity also has pronounced effects on doctor-patient interaction. Asians and Hispanics report having more unsatisfying interactions with a doctor (B= .103, p <.001; B=0.057, p <.001); however, African Americans do not have significantly more unsatisfying interactions than non-Hispanic whites.

Impact of perceived provider discrimination and unsatisfying interaction with a doctor on unmet need for health care utilization. Perceiving provider discrimination and having an unsatisfying interaction with a doctor have significant positive relationships with having an unmet need for health care utilization. The more individuals perceive provider discrimination and experience an unsatisfying interaction, the less they use health services even when needed (B=0.304; B=1.55, p <.001). The evidence was quite strong and statistically significant. Both perceived provider discrimination and unsatisfying interaction with a doctor positively affected having an unmet need for health care utilization, but the effect of perceived provider discrimination on unmet need for health care utilization was almost twice as strong as that of having an unsatisfying interaction with a doctor.

Combined impact of perceived provider discrimination and unsatisfying interaction on current poor health mediated by unmet need of health care utilization. Controlling other variables, unmet need for health care utilization directly influences poor health status (B=.157, p <.001). The indirect effects of perceived provider discrimination on poor health status through unmet need for utilization was significantly positive (B=.048, p <.001, not shown in Table 2). Mplus calculates the indirect effect by multiplying coefficients on the pathway. Mplus offers coefficients and p-values of indirect effects. The direct effect of perceived provider discrimination on poor health status was also positively significant (B=. 093, p <.001). The indirect effect of unsatisfying interaction with a doctor on current poor health through unmet need for health service utilization was significantly positive discrimination (B=.024, p <.01, not shown in Table 2), but not as strong as the indirect effect of perceived provider. The direct effect of unsatisfying interaction with a doctor on current poor health was also positively significant (B=.052, p <.05). Interestingly, there were not only significant indirect effects of perceived provider discrimination and unsatisfying interaction mediated by unmet need for health care utilization, but there were also direct effects of these variables on health status, which were almost twice as strong as the indirect effects. In addition, controlling other explanatory variables, perceived provider discrimination was a stronger predictor of poor health status than unsatisfying interaction with a doctor (B=.093 vs. B= .052, p <. 05).

Indirect effects of race/ethnicity on current poor health mediated by perceived provider discrimination and unmet need for health care utilization. Finally, based on outcomes in Table 2, we estimated the indirect effects of race/ethnicity on current poor health through perceived provider discrimination and unmet need for health service utilization (not shown in Table 2). The relationship between racial/ethnic minorities and poor physical health is mediated by perceived provider discrimination. That is, African Americans, Hispanics, and Asians have poorer health status mediated by perceived provider discrimination (African Americans: B=.011; Hispanics: B=.009; Asians: B=.007, p <.05). Likewise, the path from racial/ethnic minorities through perceived provider discrimination and then through unmet need for health care utilization to poor health status is significant for all racial/ethnic minorities (African Americans: B=.006; Hispanics: B=.005; Asians: B=.003, p <.05).

Discussion

This study investigated how perceived provider discrimination impacts health status through health care utilization and expands the understanding of how discrimination impacts health disparities through multiple pathways. Although one pathway is the biopsychosocial model,68 this current study finds support that more pathways exist through which discrimination impacts health. Although researchers hypothesize the importance of these additional pathways, namely perceived provider discrimination on health care utilization and health status9,10 no research, to our knowledge, has examined or demonstrated this impact concurrently with empirical data. Our research examines multiple racial/ethnic groups, as well as, those pathways previously speculated to impact health disparities with several significant findings.

First, individuals who perceive more provider discrimination have higher unmet needs for health care utilization, which supports Hypothesis 1. Individuals who have negative experiences within the health care setting will be less likely to continue to seek health care services, even when they report a recognized need for care. This supports previous research that perceiving discrimination in health care has a direct negative effect on health care access and utilization.10,12,13,15,16,19

Second, individuals who perceive more provider discrimination are more likely to have poor health, which supports Hypothesis 2. This relationship remains true whether examining the direct effect of perceived provider discrimination on health or the indirect effect of perceived provider discrimination on health mediated by health care utilization. Simply stated, the more provider discrimination an individual perceives, the less they will utilize health care services and subsequently, the poorer their overall health. This finding expands our knowledge and understanding regarding how discrimination impacts health status. Although previous research has found significant direct effects of discrimination on poor health status,14,20 this study finds both a direct and an indirect pathway to poor physical health, which supports the notion that perceived provider discrimination creates dissatisfaction and less trust and in turn, delays future health care utilization creating poor health for those perceiving provider discrimination.9,10

Finally, perceived provider discrimination creates health disparities in African Americans, Hispanics, and Asians through numerous pathways, which supports Hypothesis 3. Because these racial/ethnic groups perceive more provider discrimination than non-Hispanic whites, they are more likely to delay health care. In turn, this delay leads to poor health for African Americans, Hispanics, and Asians. Second, perceived provider discrimination has a direct effect on impacting poor health for African Americans, Hispanics, and Asians. Simply stated, negative experiences within the health care setting will create additional vulnerabilities in an already vulnerable population, and acts as one mechanism for creating and sustaining health disparities in African Americans, Hispanics, and Asians.

There are several possible mechanisms underlying the relationship between perceived provider discrimination and health outcomes. Providers may both intentionally or unintentionally treat patients differently because of patients’ disadvantaged social positions due to their race/ethnicity, income, education, and insurance type.28 Providers may “bring assumptions and expectations about what previous patients ‘like this one’ have been like and how those patients have understood and complied with explanations and instructions.”29(p.50) Other research supports the idea that providers who work with predominantly disadvantaged patients will experience more stress, fatigue, and inadequate support, which lead patients to report more bias in their healthcare.30 Another possible explanation is that providers work as powerful gatekeepers for advanced treatments, which may influence health disparities via such mechanisms as differential access to treatments or services and loss of benefits and rights.31 Our findings, of course, do not illuminate which of these possible mechanisms is at work, however, it is important to highlight the complex nature of perceived provider discrimination’s impact on health and the need to further refine our understanding of these mechanisms in future studies.

This study has several implications for future research, which are rooted in the limitations. First, there was no specific question to represent why individuals had limitedchealth care utilization. Although we controlled for potential reasons, such as access through health insurance and income status, future research needs to control the additional conditions, such as generational status or acculturation level, which influence the relationship between quality of medical care and health outcomes. Because there were no questions that asked about immigrant or generational status or acculturation level we were unable to control for this. In addition, due to the nature of using secondary data, this analysis is limited to general questions about perceived discrimination in the health care system and do not fully measure and likely underestimate the perceptions and experiences of minorities. The use of cross-sectional data limits our ability to causally relate and to capture how poor interaction with a doctor and perceived provider discrimination influences health outcomes. Because this is cross-sectional data, we do not exclude the possibilities that there may be a recall bias or that people who have poor health may be more likely to report that they experienced provider discrimination and unsatisfied interaction. Thus, a major challenge in future research is to apply this concept to longitudinal data, which will allow us to analyze more exact pathways and cumulative effects of perceived provider discrimination, revealing underlying mechanisms between perceived provider discrimination and health disparities among racial/ethnic groups.

These findings lend support that in addition to the biopsychosocial model explanation for how racial discrimination impacts health, provider discrimination appears to have a salient and deleterious effect on health as well. Because previous research has typically not turned its attention towards other mechanisms that create and sustain health disparities in racial/ethnic minority groups, the aspects of perceived provider discrimination on health disparities have been neglected. These research findings, that African Americans, Hispanics, and Asians all perceive provider discrimination which negatively impacts their health, suggest that perceiving provider discrimination impacts individuals utilizing medical care. This delay in obtaining medical care then negatively impacts health of racial and ethnic minorities, thereby exacerbating health disparities.

This study makes unique contributions to the literature on perceived provider discrimination and lends itself well to policy implications. These findings illustrates the need to reduce discrimination in health care. This reduction, which could take place through cultural awareness for providers,13 culturally competent interventions in the health care setting,13 and culturally concordant patient-physician matching,32 would target those populations who are most at risk both for perceiving provider discrimination and poor health. Because perceived provider discrimination has been linked to negative health outcomes, a reduction in perceived provider discrimination could play a role in reducing health disparities experienced by racial and ethnic minorities. In conclusion, by understanding how perceived provider discrimination impacts health status, these findings will enrich our understanding of how racial/ethnic health disparities are created and sustained, and thus provide a concrete mechanism for future policy interventions with health care providers that can help to reduce these health disparities.

Acknowledgements

The project described was supported by Grant Number P20MD002316 from the National Center On Minority Health And Health Disparities. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center On Minority Health And Health Disparities or the National Institutes of Health.

Contributor Information

Chioun Lee, Southwest Interdisciplinary Research Center, Arizona State University. Department of Sociology, Rutgers University.

Stephanie L. Ayers, Southwest Interdisciplinary Research Center, Arizona State University.

Jennie Jacobs Kronenfeld, School of Social and Family Dynamics, Arizona State University.

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