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Health professional organizations have advocated for increasing the “cultural competence” (CC) of healthcare providers, to reduce racial and ethnic disparities in patient care. It is unclear whether provider CC is associated with more equitable care.
To evaluate whether provider CC is associated with quality of care and outcomes for patients with HIV/AIDS.
Survey of 45 providers and 437 patients at four urban HIV clinics in the U.S.
Providers’ self-rated CC was measured using a novel, 20-item instrument. Outcome measures included patients’ receipt of antiretroviral (ARV) therapy, self-efficacy in managing medication regimens, complete 3-day ARV adherence, and viral suppression.
Providers’ mean age was 44 years; 56 % were women, and 64 % were white. Patients’ mean age was 45; 67 % were men, and 77 % were nonwhite. Minority patients whose providers scored in the middle or highest third on self-rated CC were more likely than those with providers in the lowest third to be on ARVs, have high self-efficacy, and report complete ARV adherence. Racial disparities were observed in receipt of ARVs (adjusted OR, 95 % CI for white vs. nonwhite: 6.21, 1.50–25.7), self-efficacy (3.77, 1.24–11.4), and viral suppression (13.0, 3.43–49.0) among patients of low CC providers, but not among patients of moderate and high CC providers (receipt of ARVs: 0.71, 0.32–1.61; self-efficacy: 1.14, 0.59–2.22; viral suppression: 1.20, 0.60–2.42).
Provider CC was associated with the quality and equity of HIV care. These findings suggest that enhancing provider CC may reduce racial disparities in healthcare quality and outcomes.
Human immunodeficiency virus (HIV) infection is a leading contributor to racial inequalities in health and life expectancy in the United States.1–3 These disparities arise in part from the fact that minority Americans receive lower quality medical care than whites.4,5 Studies have demonstrated that minority individuals with HIV/AIDS are less likely than whites to receive antiretroviral (ARV) therapy6,7 and to adhere to ARV regimens once prescribed.8–11 Disparities in HIV management lead directly to disparities in outcomes, including viral suppression, progression to AIDS, and death.10–15
Although disparities in HIV care and outcomes are multifactorial in origin, the patient–provider relationship plays a critical role. The strength of patient–provider relationships is associated with greater patient trust and self-efficacy, and in turn, a higher likelihood of patients’ receiving ARV therapy, adhering to ARV regimens, and achieving favorable virologic outcomes.16–20 Unfortunately, many minority patients face a disadvantage in establishing strong relationships with their providers. Most minorities in the U.S. see providers from racial and ethnic groups different from their own.21 Minority patients tend to have better relationships with, and may therefore receive higher quality care from, primary care providers (PCPs) of their own race or ethnicity.22–24 In a national study of HIV care, delays in the initiation of protease inhibitors were observed among African Americans with race discordant providers, but not among those with race concordant providers.25
Acknowledging that patient–provider relationships might contribute to racial disparities, health professional organizations have advocated for healthcare providers to increase their “cultural competence” (CC),5,26–29 i.e., their effectiveness in caring for patients from diverse backgrounds.30 Although appealing in concept, the promise of increasing provider CC remains unclear, because there has been limited evaluation of whether CC is associated with better or more equitable patient care and outcomes.
We sought to evaluate whether CC among HIV care providers was associated with better care and outcomes for patients with HIV/AIDS. Specifically, we hypothesized that provider CC would be associated with patients’ receipt of ARV therapy, self-efficacy in managing medications, ARV adherence, and viral suppression. We also examined whether provider CC mitigated racial disparities in these outcome measures.
We designed the Enhancing Communication and HIV Outcomes (ECHO) Study to evaluate the role of the patient–provider relationship in racial/ethnic disparities in HIV care and outcomes.31–33 Subjects were PCPs and their patients at four outpatient HIV care sites (Baltimore, Detroit, New York, and Portland, OR) participating in the HIV Research Network.34 The study received Institutional Review Board approval from each site. Eligible providers were physicians, nurse practitioners, or physician assistants who provided primary care to HIV-infected patients. Eligible patients were HIV-infected, 19 years or older, English-speaking, and had had at least one prior visit with their provider. Data were collected between October 2006 and June 2007.
All eligible providers at the four sites were invited to participate in the study. Providers who agreed to participate and gave informed consent completed a baseline questionnaire. Research assistants (RAs) approached patients of participating providers in clinic waiting rooms, with the goal of enrolling ten patients per provider. For most providers, the actual number of patients recruited ranged from five to 15. Providers also completed post-encounter surveys for each enrolled patient. Providers received a $250 incentive for participation. Based on the expected distribution of patients by race/ethnicity at the four study sites, we attempted to enroll equal numbers of African American and white patients for each provider at two sites (Baltimore and Detroit), and equal numbers (about one-third each) of African American, white, and Latino patients for each provider at the other two sites (Portland and New York). Following the medical encounter, RAs obtained informed consent from a convenience sample of each participating provider’s patients and administered a one-hour interview, assessing demographic, social, attitudinal, and behavioral characteristics, and ARV adherence. Patients received a $50 incentive for participation. We abstracted clinical data, including ARV regimens, and CD4 counts and HIV RNA levels measured within 3 months of the interview, from patients’ medical records.
We asked patients and PCPs to indicate—from a list of options including White/Caucasian, Black/African American, Hispanic/Latino, American Indian/Alaska Native, Asian, Pacific Islander/Native Hawaiian, or Other—the primary racial/ethnic group with which they identified.
To measure provider CC, we initially sought existing instruments, but found none with sufficient face validity for use among PCPs.35 Many prior instruments focus on personal characteristics and traits, rather than role-specific knowledge, attitudes and skills as health professionals. We therefore developed a novel measure. We first conducted a systematic review of 29 published conceptual models describing the concept of healthcare provider CC. Three reviewers abstracted distinct concepts that represented components of CC described by authors. Through iterative discussion of these components and their definitions, the reviewers developed a framework outlining core dimensions of CC that included domains of provider awareness and attitudes— about the concept of culture, the relevance of sociocultural context in patient care, disparities in health and health care, and diverse health beliefs and behaviors—and provider skills and behaviors—in cross-cultural care and patient-centered communication. We then developed a pool of survey items representing these dimensions. Two investigators (SS, MCB) selected 27 items that had the greatest relevance to physicians providing primary care (Appendix). Because the different dimensions of CC were not completely distinct, there was overlap in the content of items across dimensions, and the selected items were chosen to represent CC broadly, rather than to constitute subscales measuring distinct CC dimensions. Of the 27 selected items, seven were subsequently dropped due to highly skewed responses suggesting ceiling effects, leaving a final set of 20 items. All items were statements with which providers rated their level of agreement, using a 6-point Likert scale.
Patients were considered to be on ARV therapy if they were on medications recommended by national guidelines for HIV treatment at the time of data collection.36 We used a previously validated, six-item scale to measure patients’ self-efficacy in managing their HIV medication regimens.37 We defined ARV adherence, according to the Adult AIDS Clinical Trials Group method,38 as patients’ reporting not having missed any ARV medication doses within the previous three days.39 Finally, based on the limits of detection for viral load at our sites, we considered a patient’s viral load to be suppressed if it was at or below 75 RNA copies per mL.36
In addition to race/ethnicity, providers reported their age, gender, and profession (physician vs. non-physician). Patients reported age, gender, level of education, marital status, and employment. We measured patients’ health literacy using the Rapid Evaluation of Adult Literacy in Medicine (REALM).40 We assessed substance use with the Addiction Severity Index-Lite41 and calculated substance use severity scores using a weighted algorithm validated as a predictor of ARV adherence.42 Patients rated their quality of life using a single, global item with a 100 mm visual analogue scale.43 They reported depressive symptoms using the 10-item Center for Epidemiologic Studies depression scale (CES-D).44 Finally, we measured social support using a 9-item scale from the HIV Cost and Services Utilization Study.45
The score distribution for the CC scale was moderately skewed. We accordingly divided scores into tertiles to accommodate this skewed distribution in our analyses, while still allowing for evaluation of graded associations with our outcome variables. Similarly, because of skewed response distributions, and to enable multivariable logistic regression analyses, we dichotomized medication self-efficacy between the highest possible value and all others.
We compared provider and patient covariates across provider CC tertiles, our primary independent variable, using Pearson’s chi-square tests or one-way analysis of variance, as appropriate. Covariates that differed (p< 0.10) across provider CC tertiles were included in multivariable analyses. To test the association between provider CC and our outcome variables, we developed multivariable logistic regression models using generalized estimating equations to account for clustering of patients within providers. These models were adjusted for study site; provider gender; patient age, gender, marital status, and employment status; and patient–provider race concordance. Analyses of receipt of ARV therapy also included CD4 count (≤ 350 vs. > 350 cells/mm3) as a covariate, based on national guidelines for ARV initiation.36 Analyses for adherence were limited to patients on ARV therapy, and for viral suppression to patients either on or eligible (CD4 count ≤ 350 cells/mm3) for ARV therapy. We included patients whom we considered eligible for ARV therapy in our viral suppression analyses, even if they were not on ARV therapy, to account for the impact that differences in appropriate use of ARV medications may have on disparities in HIV-related outcomes. We conducted regression analyses first for all patients in the sample, and then for racial/ethnic subgroups, including whites, all nonwhites (predominantly African Americans and Latinos), and African Americans alone. The Latino subgroup was too small for separate analysis.
To test for racial disparities, we compared outcomes by race in both unadjusted and adjusted GEE-based logistic regression models. In adjusted models, we included study site, as well as variables that differed (p< 0.10) between whites and nonwhites: provider race and profession (non-physician vs. physician), and patient age, gender, education level, employment status, health literacy, substance use severity, and quality of life. To evaluate the hypothesis that provider CC mitigates racial disparities, we tested for interactions between patient race and provider CC. Where interactions were significant, we evaluated the association of race with the outcome variable, stratified by provider CC. To allow for stability of stratified multivariable models, we collapsed CC tertiles into two categories, low vs. middle/high. We chose this dichotomy based on findings from our primary analyses that the major differences across CC tertiles were between the lowest and the two higher categories.
All analyses were conducted using Stata/SE version 9.0 (StataCorp, College Station, Texas).
There were 55 providers eligible for the study across all sites. Overall, 45 (82 %) agreed to participate. Two refused; the other eight were not approached because we reached our enrollment target. Of 617 eligible patients, 437 (71 %) agreed to participate and completed the post-encounter survey, including 250 African American, 60 Latino, and 101 white patients, and 26 from other racial/ethnic groups.
Our CC scale had a Cronbach’s alpha of 0.76 (average inter-item correlation 0.15, item-scale correlations ranging from 0.17 to 0.69). The mean CC score among providers was 4.67 (SD .51), from a possible range of 1 to 6. Provider and patient characteristics, stratified by CC tertiles, are displayed in Table 1. Among providers, men were more likely than women to be in the low CC group (p=0.03). Patient–provider race concordance was associated with higher provider CC, primarily because the majority of patients in the sample were African American, and both African American providers in our study had high CC scores.
In unadjusted comparisons among all patients, we found no significant differences in any outcome variable by provider CC (Table 1). However, after adjusting for CD4 count and other clinical and demographic variables, we found that nonwhite patients seeing moderate to high CC providers were more likely to be on ARV therapy than those with low CC providers (Table 2). Provider CC was also independently associated with nonwhite patients’ self-efficacy and medication adherence. In general, nonwhite patients with low CC providers reported less self-efficacy and lower medication adherence than those with moderate to high CC providers. Comparisons of moderate and high CC levels were not significant, but the pattern of findings differed qualitatively across outcomes. Nonwhite patients’ self-efficacy increased monotonically with increasing provider CC. In contrast, adherence was highest among patients seeing providers in the middle CC tier. Among white patients, provider CC was negatively associated with medication self-efficacy and adherence, though the latter association was not significant.
Consistent with the data for adherence, the association of provider CC with patients’ viral suppression was positive for nonwhites and negative for whites, though these associations were not significant. In analyses restricted to African Americans, however, we observed a graded association, with better virologic outcomes for patients of high CC providers.
In comparing outcomes by patient race, we found no disparities in receipt of ARV therapy. However, nonwhites (74 % of whom were African American) had lower self-efficacy and adherence, and less adequate control of viremia than white patients did (Table 3). After adjusting for potential confounders, the disparity in patient self-efficacy was similar in magnitude but no longer significant; all other differences persisted. Interaction analyses revealed that the association of patient race with medication adherence did not vary significantly by provider CC (p=0.10 for patient race-provider CC interaction), but receipt of ARV therapy, self-efficacy, and viral suppression did vary by provider CC (p for interactions = .024, .026, and .006 for receipt of ARV therapy, self-efficacy, and viral suppression, respectively). Stratified analyses revealed that racial disparities in each of these 3 outcomes were confined to low CC providers (Table 4). Among low CC providers, nonwhite patients had 6-fold lower odds of being on ARV therapy, 4-fold lower odds of having high medication self-efficacy, and 13-fold lower odds of having their viral load suppressed, compared to white patients. These findings were similar or more dramatic when comparing African Americans to whites. In contrast, among providers with moderate to high levels of CC, we observed no racial disparities in any patient outcome measure.
In response to evidence that both health and health care are inequitably distributed among racial and ethnic groups in the U.S., health professional organizations have called for increased “cultural competence” among healthcare providers.26–29 These recommendations have been largely based on expert opinions about the theoretical benefits of CC, rather than empirical research. We developed a novel instrument to measure some of the diverse dimensions of awareness, attitudes, skills, and behaviors that have been collectively referred to as “cultural competence.” Higher scores on our measure among PCPs in HIV care settings were associated with more equitable care and outcomes across racial/ethnic groups. Among low CC providers, we observed substantial racial disparities in receipt of ARV therapy, patients’ self-efficacy in managing medications, and viral suppression. Among providers with moderate or high CC, we found no racial disparities. These findings provide empirical support for the assertion that greater provider CC may reduce racial/ethnic disparities in health care quality and outcomes.
Greater equity in our study largely resulted from positive associations between provider CC and outcomes among minority patients. However, we also found an unexpected, negative association between provider CC and outcomes among white patients. It is possible that our bidirectional findings for nonwhite and white patients resulted in part from different preferences for provider interaction style. High scores on our CC measure may have captured, in part, a provider orientation to patient care that has been referred to as “relationship-centered.”46,47 This orientation may be particularly valued by cultural groups, including many ethnic minorities, that prefer close relationships with health care providers and more personal interactions with social and emotional content.48,49 In contrast, European Americans may on average prefer, or be more tolerant of, a more transactional form of patient–provider relationship, in which interactions are dominated by exchanges of biomedical information.49
Our study had several limitations. We developed a novel CC measure not tested in prior studies. Because our sample included only 45 providers, we could not perform analyses (e.g., factor analysis) to establish the construct validity of the instrument or empirically derive subscales. We did, however, develop our measure using qualitative methods to derive concepts described in the published literature, and our multidimensional instrument likely captures a more theoretically grounded and robust set of CC dimensions than prior studies that have used only two to three items or composites of items from multiple existing instruments.50–53 In addition, our finding that CC scores were associated with better outcomes among minority but not white patients, and that racial disparities were less prominent among patients of higher CC providers, offers supportive evidence that our instrument measures a construct that predicts the major goals of CC, i.e., effectiveness in caring for minority patients and reducing racial and ethnic disparities in health care quality.
The diversity of items in our measure was both a strength and a limitation. The inclusion of multiple dimensions allowed us to capture a broader conceptualization of CC than other studies. However, this resulted in a scale that had only a moderate level of internal consistency. Larger provider samples will be needed to conduct further analyses to refine and empirically specify discrete dimensions contained within our multidimensional instrument.
Our measure also included only interpersonal dimensions of CC. Separate instruments and study designs will be needed to evaluate how system or organization-level CC affects quality and equity of health care.30 Finally, our study included only persons with HIV/AIDS and their PCPs. The extent to which our findings are generalizable to other settings, patients, and providers may depend on the similarity of those settings to ours in terms of the influence of race, ethnicity, and patient–provider relationships on healthcare processes and outcomes.
Acknowledging these limitations, we believe our results have important implications. Although CC has been heavily promoted in recent years,5,26–29 there has been little empirical evidence to inform what constitutes CC or to evaluate whether it is associated with better patient care. A recent study demonstrated that higher scores on attitudinal and behavioral scales similar in content to many of our items were associated with higher patient ratings of interpersonal care and greater patient involvement in care.50 Our study extends these findings by demonstrating that provider CC is associated with higher quality of care, better patient self-management, and better health outcomes, among minority patients. If validated in future studies and in other care settings, our instrument might serve as an evidence-based tool to evaluate CC among health professionals. Our study also provides support for the notion that increasing healthcare provider CC, whether through training interventions or through efforts to diversify the healthcare workforce, holds the potential to reduce racial disparities in both the quality of health care and the health of diverse patient populations.
This research was supported by a contract from the Health Resources and Services Administration and the Agency for Healthcare Research and Quality (AHRQ 290-01-0012). Representatives of both funding agencies were involved in the design of the study, but not in its conduct; in collection, management, analysis, or interpretation of the data; or in preparation, review, or approval of the manuscript. Drs. Saha, Moore, and Beach had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Dr. Saha was supported by the Department of Veterans Affairs. Dr. Beach was supported by the Agency for Healthcare Research and Quality (K08 HS013903-05), and both Drs. Saha and Beach were supported by Generalist Physician Faculty Scholar awards from the Robert Wood Johnson Foundation. Dr. Korthuis was supported by the National Institute on Drug Abuse (K23 DA019809). The views expressed in this article are those of the authors, and no official endorsement by the Agency for Healthcare Research and Quality, the Department of Veterans Affairs, or the U.S. Department of Health and Human Services is intended or should be inferred.
The authors declare that they do not have a conflict of interest.