Abstract
Objective
To examine the relationship between perceived discrimination and preventive health care utilization.
Design and Participants
Cross-sectional analysis using the 2004 Behavioral Risk Factor Surveillance System “Reactions to Race” module ( = 28,839).
Measurements
Outcomes were self-reported utilization of seven preventive health services. Predictors included perceived negative and positive racial discrimination (vs. none) while seeking health care in the past year. Multivariable models adjusted for additional patient characteristics.
Main Results
In unadjusted models, negative discrimination was significantly associated with less utilization of mammogram, pap test, PSA test, blood stool test, and sigmoidoscopy/colonoscopy (ORs = 0.53–0.73, p < .05), but not flu or pneumococcal vaccines (ORs = 0.76 and 0.84). Positive discrimination was significantly associated with more utilization of all services (ORs = 1.29–1.58, p < .05) except pap test (OR = 0.94). In adjusted models, neither negative nor positive discrimination was predictive of utilization, except for PSA test (positive discrimination OR = 1.33, p < .05).
Conclusions
Perceived racial discrimination in health care does not independently predict preventive health care utilization.
KEY WORDS: perceived discrimination, preventive health, behavioral risk factor surveillance system, centers for disease control and prevention
INTRODUCTION
People who perceive racial discrimination are at greater risk for poor mental and physical health.1 Mechanisms connecting perceived discrimination and health, however, are not yet well-understood. Proposed mechanisms are based primarily on the biopsychosocial model of discrimination, in which discrimination negatively affects health by causing a physiological stress response in the body.2,3 This model explains biological underpinnings of the discrimination-health link, but it does not address the possibility that discrimination can also affect health by shaping health behaviors. For example, perceiving discrimination in health care settings may cause patients to avoid engaging the health care system, which could lead to sub-optimal care and poor health outcomes. To determine whether patient health behavior is a plausible mechanism by which discrimination affects health, it is important to examine the relationship between perceived discrimination in health care and health care utilization.
Although prior studies have demonstrated that perceived discrimination is associated with delays in seeking necessary medical care,4–6 delays in obtaining prescriptions, treatments, or tests,4,7 and substituting alternative medicine for conventional care,8 evidence regarding the relationship between discrimination and use of preventive health services such as vaccinations or recommended screenings has been mixed.6,9,10 Therefore, the purpose of the current study was to examine the association between perceived discrimination in health care and utilization of preventive health services. A unique feature of this study is that we examined the association of both negative and positive discriminatory experiences with utilization, whereas past studies have only focused on negative discriminatory experiences. That is, we examined utilization for patients who perceived they were treated better than members of other races as well as for patients who perceived worse treatment.
METHODS
Source of Data
The Behavioral Risk Factor Surveillance System (BRFSS), which we used for this analysis, is an annual telephone survey designed to monitor health conditions and risk behaviors of U.S adults.11 The current analyses included 2004 BRFSS data from states that administered the “Reactions to Race” module (i.e., Colorado, Delaware, Mississippi, Rhode Island, South Carolina, Wisconsin, and Washington, DC), which included a question regarding racial discrimination in health care.
Study Measures
The outcomes included self-reported utilization of seven preventive health services: 1) flu shot in the past year for people 65 or older, 2) pneumococcal vaccine for people 65 or older, 3) mammogram in the past 2 years for women 40 or older, 4) pap test in the past 3 years for women 18 or older, 5) PSA test in the past 2 years for men 50 or older, 6) blood stool test in the past 2 years for people 50 or older, and 7) either a sigmoidoscopy or colonoscopy in the past two years for people 50 or older.
The primary predictor was perceived racial discrimination in health care, assessed as follows: “Within the past 12 months when seeking health care, do you feel your experiences were worse than, the same as, or better than for people of other races?” The following were the response options: Worse than other races; The same as other races; Better than other races; Worse than some races, better than others; or, Only encountered people of the same race. The first three responses represented negative discrimination, no discrimination, and positive discrimination, respectively. The last two responses were excluded from analyses due to low prevalence (0.3% each).
The following patient characteristics were included as covariates to control for their potential relationships with health care utilization: race/ethnicity, sex, age, household income, education, health care coverage, affordability of medical care, self-reported health status, and state. Health care coverage was assessed with the item, “Do you have any kind of health care coverage, including health insurance, prepaid plans such as HMOs, or government plans such as Medicare? (Yes, No).” Affordability of medical care was assessed with the item, “Was there a time in the past 12 months when you needed to see a doctor but could not because of the cost? (Yes, No).”
Statistical Analyses
State-level data weights developed by BRFSS were applied prior to all analyses. We examined the bivariate association between perceived discrimination and each preventive measure. We then used multivariable logistic regression models to assess the association between perceived discrimination and each preventive measure, controlling for patient characteristics. Additional models tested for interactions between race/ethnicity and perceived discrimination, which were not significant and will not be discussed further.
Because race/ethnicity is closely related to perceived discrimination,12 we avoided confounding race and perceived discrimination by re-running the multivariable models with all covariates except race/ethnicity. Given that omitting race/ethnicity did not change the relationship between perceived discrimination and any of the outcomes, we report the models that included race/ethnicity.
All analyses were done using STATA/SE 9.2 for Windows. This study was approved by the VA Pittsburgh Healthcare System Institutional Review Board.
RESULTS
Characteristics of the sample are provided in Table 1. Overall, 3.0% of the sample perceived negative racial discrimination while seeking health care in the past 12 months, 82.5% perceived no discrimination, and 14.5% perceived positive discrimination. For all but one preventive measure (pap test), utilization was lowest among people who perceived negative discrimination and highest among those who perceived positive discrimination (Table 2). In unadjusted analyses (Table 2), utilization among those who perceived negative discrimination (vs. none) was significantly lower for mammogram, pap test, PSA test, blood stool test, and sigmoidoscopy/colonoscopy ( < .05), but not for flu shot or pneumococcal vaccine. In contrast, utilization was significantly higher among those who perceived positive discrimination (vs. none) for all preventive measures except pap test. In multivariable analyses adjusting for patient characteristics, however, neither negative nor positive discrimination significantly predicted utilization of any of the preventive measures, except PSA test (Table 2). Utilization of PSA was higher among those who perceived positive discrimination (vs. none; < .05). Full details of the adjusted models are available in Appendices A, B and C.
Table 1.
Characteristics of the Study Sample*
| Males | Females | Total | |
|---|---|---|---|
| Unweighted | 6,666 | 22,173 | 28,839 |
| Weighted | 2,789,916 | 8,252,728 | 11,042,644 |
| Variable | Column percentage unless otherwise noted | ||
| Perceived discrimination in health care | |||
| Negative discrimination | 2.8 | 3.1 | 3.0 |
| No discrimination | 80.4 | 83.2 | 82.5 |
| Positive discrimination | 16.9 | 13.7 | 14.5 |
| Race/Ethnicity | |||
| Non-Hispanic white | 86.8 | 79.6 | 81.5 |
| Non-Hispanic African American | 10.1 | 15.1 | 13.8 |
| Hispanic American | 3.0 | 5.3 | 4.7 |
| Sex | |||
| Female | – | – | 74.7 |
| Male | – | – | 25.3 |
| Age (mean, standard deviation) | 63.0(0.17) | 46.5(0.18) | 50.7(0.16) |
| Income | |||
| <$15 K | 8.9 | 12.8 | 11.8 |
| $15 K–$25 K | 15.6 | 19.3 | 18.3 |
| $25 K–$35 K | 15.4 | 15.1 | 15.1 |
| $35 K–$50 K | 18.8 | 16.8 | 17.3 |
| >$50 K | 41.3 | 36.0 | 37.4 |
| Education | |||
| Less than HS | 11.5 | 10.3 | 10.6 |
| HS graduate | 30.2 | 32.8 | 32.1 |
| Some college | 22.3 | 27.8 | 26.4 |
| College degree | 36.1 | 29.1 | 30.9 |
| Health care coverage | |||
| Yes | 91.6 | 87.1 | 88.3 |
| No | 8.4 | 12.9 | 11.7 |
| Affordability of medical care: Was medical care cost-prohibitive in last 12 months? | |||
| No | 92.6 | 85.3 | 87.2 |
| Yes | 7.4 | 14.7 | 12.8 |
| Health status | |||
| Excellent, very good, or good | 77.1 | 83.4 | 81.8 |
| Fair or poor | 22.9 | 16.6 | 18.2 |
| State | |||
| AK | 13.0 | 12.1 | 12.4 |
| CO | 19.2 | 19.7 | 19.6 |
| DE | 3.9 | 3.8 | 3.8 |
| DC | 2.2 | 2.6 | 2.5 |
| MS | 12.4 | 13.2 | 13.0 |
| RI | 5.1 | 5.1 | 5.1 |
| SC | 18.7 | 18.8 | 18.8 |
| WI | 25.4 | 24.5 | 24.8 |
*Characteristics of the male and female samples are described separately because a) the sample included males aged 40 and older and females aged 18 and older, and b) most of the preventive measures are sex-specific
Table 2.
The Association Between Perceived Discrimination and Utilization of Preventive Measures
| Preventive measure | Perceived discrimination | Obtained measure (%) | Crude OR (95% CI) | Adjusted OR (95% CI)† |
|---|---|---|---|---|
| Flu shot | Negative | 65 | 0.76 (0.45,1.27) | 0.98 (0.58,1.65) |
| None | 71 | Reference | ||
| Positive | 78 | 1.46 (1.18,1.80)* | 1.12 (0.87,1.44) | |
| Pneumococcal vaccine | Negative | 61 | 0.84 (0.49,1.44) | 0.99 (0.53,1.84) |
| None | 65 | Reference | ||
| Positive | 73 | 1.47 (1.20,1.80)* | 1.23 (0.97,1.57) | |
| Mammogram | Negative | 62 | 0.62 (0.47,0.81)* | 1.05 (0.76,1.45) |
| None | 73 | Reference | ||
| Positive | 78 | 1.36 (1.15,1.60)* | 1.14 (0.94,1.37) | |
| Pap test | Negative | 80 | 0.53 (0.38,0.74)* | 0.67 (0.45,1.00) |
| None | 88 | Reference | ||
| Positive | 87 | 0.94 (0.75,1.19) | 0.87 (0.65,1.15) | |
| PSA test | Negative | 53 | 0.61 (0.39,0.97)* | 0.93 (0.59,1.48) |
| None | 65 | Reference | ||
| Positive | 75 | 1.58 (1.24,2.02)* | 1.33 (1.02,1.75)* | |
| Blood stool test | Negative | 19 | 0.65 (0.45,0.92)* | 0.83 (0.56,1.24) |
| None | 27 | Reference | ||
| Positive | 32 | 1.29 (1.13,1.48)* | 1.12 (0.96,1.30) | |
| Sigmoidoscopy/ colonoscopy | Negative | 45 | 0.73 (0.56,0.96)* | 1.22 (0.88,1.68) |
| None | 53 | Reference | ||
| Positive | 62 | 1.42 (1.25,1.62)* | 1.11 (0.96,1.29) |
*p < .05
†Adjusted for race/ethnic group, sex, age, income, education, health care coverage, affordability of medical care, health status, and state
APPENDIX A.
Association of Perceived Discrimination with Obtaining Flu and Pneumococcal Vaccinations, Adjusted for Covariates
| Predictors | Preventive measure | ||
|---|---|---|---|
| FLU | PNE | ||
| Perceived discrimination in health care | Omnibus | 0.66 | 0.22 |
| Worse | 0.98 (0.58,1.65) | 0.99 (0.53,1.84) | |
| Better | 1.12 (0.87,1.44) | 1.23 (0.97,1.57) | |
| Race/Ethnicity | Omnibus | 0.005 | <0.001 |
| Hispanic | 0.96 (0.53,1.73) | 0.86 (0.51,1.44) | |
| African American | 0.62 (0.47,0.83) | 0.45 (0.33,0.60) | |
| Sex | Omnibus | 0.05 | 0.33 |
| Male | 1.21 (1.00,1.48) | 0.91 (0.75,1.10) | |
| Age | Omnibus | <0.001 | <0.001 |
| (Continuous) | 1.03 (1.02,1.05) | 1.06 (1.05,1.08) | |
| Income | Omnibus | 0.19 | 0.63 |
| Less than $15 K | 0.65 (0.45,0.94) | 0.92 (0.65,1.30) | |
| $15 K–$25 K | 0.81 (0.57,1.13) | 0.94 (0.68,1.29) | |
| $25 K–$35 K | 0.89 (0.63,1.26) | 0.99 (0.72,1.35) | |
| $35 K–$50 K | 0.88 (0.64,1.22) | 1.17 (0.87,1.59) | |
| Education | Omnibus | 0.50 | 0.52 |
| Less than HS | 0.78 (0.55,1.11) | 0.81 (0.58,1.13) | |
| HS graduate | 0.93 (0.70,1.23) | 0.97 (0.74,1.27) | |
| Some college | 0.87 (0.65,1.17) | 1.01 (0.76,1.34) | |
| Healthcare coverage | Omnibus | 0.17 | 0.15 |
| No | 0.67 (0.38,1.19) | 0.66 (0.37,1.16) | |
| Medical care cost prohibitive | Omnibus | 0.58 | 0.90 |
| Yes | 0.89 (0.58,1.36) | 1.03 (0.67,1.58) | |
| Health status | Omnibus | <0.001 | <0.001 |
| Fair or poor | 1.51 (1.21,1.87) | 1.55 (1.26,1.92) | |
| State | Omnibus | 0.007 | 0.21 |
| CO | 1.62 (1.14,2.29) | 1.43 (1.04,1.95) | |
| DE | 0.93 (0.65,1.34) | 1.22 (0.85,1.75) | |
| DC | 0.73 (0.48,1.10) | 1.18 (0.78,1.79) | |
| MS | 0.92 (0.69,1.23) | 1.37 (1.04,1.80) | |
| RI | 1.09 (0.78,1.52) | 1.27 (0.93,1.74) | |
| SC | 1.25 (0.93,1.69) | 1.49 (1.12,1.97) | |
| WI | 1.00 (0.73,1.38) | 1.32 (0.97,1.79) | |
Numbers shown are odds ratios and 95% confidence intervals, unless otherwise noted. FLU = flu shot, PNE = pneumococcal vaccine.
APPENDIX B.
Association of Perceived Discrimination with Obtaining Screenings for Breast, Cervical, and Prostate Cancer, Adjusted for Covariates
| Predictors | Preventive measure | |||
|---|---|---|---|---|
| MAM | PAP | PSA | ||
| Perceived discrimination in health care | Omnibus | 0.38 | 0.10 | 0.10 |
| Worse | 1.05 (0.76,1.45) | 0.67 (0.45,1.00) | 0.93 (0.59,1.48) | |
| Better | 1.14 (0.94,1.37) | 0.87 (0.65,1.15) | 1.33 (1.02,1.75) | |
| Race/Ethnicity | Omnibus | <0.001 | <0.001 | 0.02 |
| Hispanic | 1.12 (0.78,1.61) | 1.76 (1.16,2.66) | 0.70 (0.44,1.12) | |
| African American | 1.60 (1.33,1.92) | 1.85 (1.45,2.37) | 1.51 (1.06,2.16) | |
| Age | Omnibus | <0.001 | <0.001 | <0.001 |
| (Continuous) | 1.03 (1.02,1.04) | 0.98 (0.97,0.99) | 1.05 (1.03,1.06) | |
| Income | Omnibus | <0.001 | <0.001 | <0.001 |
| Less than $15 K | 0.31 (0.24,0.39) | 0.36 (0.26,0.50) | 0.51 (0.35,0.74) | |
| $15 K–$25 K | 0.44 (0.36,0.53) | 0.46 (0.35,0.61) | 0.51 (0.37,0.70) | |
| $25 K–$35 K | 0.63 (0.52,0.78) | 0.61 (0.45,0.84) | 0.64 (0.48,0.86) | |
| $35 K–$50 K | 0.74 (0.61,0.89) | 0.78 (0.57,1.06) | 0.81 (0.62,1.05) | |
| Education | Omnibus | 0.09 | <0.001 | <0.001 |
| Less than HS | 0.75 (0.59,0.96) | 0.35 (0.23,0.53) | 0.43 (0.30,0.61) | |
| HS graduate | 0.84 (0.71,1.00) | 0.46 (0.36,0.60) | 0.75 (0.58,0.96) | |
| Some college | 0.92 (0.78,1.10) | 0.75 (0.57,0.98) | 0.89 (0.70,1.15) | |
| Healthcare coverage | Omnibus | 0.002 | 0.05 | <0.001 |
| No | 0.72 (0.58,0.88) | 0.78 (0.60,1.00) | 0.51 (0.37,0.69) | |
| Medical care cost prohibitive | Omnibus | <0.001 | <0.001 | 0.13 |
| Yes | 0.63 (0.52,0.75) | 0.61 (0.48,0.77) | 0.77 (0.55,1.08) | |
| Health status | Omnibus | 0.25 | 0.87 | 0.12 |
| Fair or poor | 1.10 (0.94,1.29) | 1.02 (0.82,1.27) | 1.21 (0.95,1.54) | |
| State | Omnibus | <0.001 | 0.02 | 0.001 |
| CO | 1.10 (0.89,1.35) | 1.52 (1.12,2.05) | 1.07 (0.79,1.45) | |
| DE | 1.98 (1.51,2.60) | 1.63 (1.13,2.35) | 1.49 (1.05,2.14) | |
| DC | 1.26 (0.94,1.69) | 1.19 (0.82,1.72) | 1.31 (0.85,1.99) | |
| MS | 0.96 (0.80,1.16) | 1.19 (0.91,1.56) | 1.29 (0.96,1.73) | |
| RI | 2.09 (1.65,2.66) | 1.65 (1.19,2.29) | 1.40 (1.01,1.95) | |
| SC | 1.15 (0.95,1.39) | 1.49 (1.13,1.98) | 1.50 (1.13,1.99) | |
| WI | 1.28 (1.04,1.58) | 1.34 (1.00,1.78) | 0.83 (0.62,1.11) | |
Numbers shown are odds ratios and 95% confidence intervals, unless otherwise noted. MAM = Mammogram, PAP = Pap test, PSA = PSA test
APPENDIX C.
Association of Perceived Discrimination with Obtaining Screenings for Colon Cancer, Adjusted for Covariates
| Predictors | Preventive measure | ||
|---|---|---|---|
| BST | SIG | ||
| Perceived discrimination in health care | Omnibus | 0.22 | 0.20 |
| Worse | 0.83 (0.56,1.24) | 1.22 (0.88,1.68) | |
| Better | 1.12 (0.96,1.30) | 1.11 (0.96,1.29) | |
| Race/Ethnicity | Omnibus | 0.18 | 0.03 |
| Hispanic | 0.72 (0.49,1.07) | 0.95 (0.69,1.30) | |
| African American | 1.07 (0.88,1.30) | 0.80 (0.67,0.94) | |
| Sex | Omnibus | 0.004 | 0.02 |
| Male | 1.18 (1.05,1.33) | 0.88 (0.79,0.97) | |
| Age | Omnibus | <0.001 | <0.001 |
| (Continuous) | 1.03 (1.03,1.04) | 1.05 (1.04,1.06) | |
| Income | Omnibus | 0.55 | 0.01 |
| Less than $15 K | 0.86 (0.69,1.08) | 0.72 (0.59,0.89) | |
| $15 K–$25 K | 0.91 (0.75,1.11) | 0.76 (0.63,0.91) | |
| $25 K–$35 K | 0.99 (0.82,1.19) | 0.82 (0.69,0.98) | |
| $35 K–$50 K | 1.04 (0.88,1.24) | 0.91 (0.78,1.07) | |
| Education | Omnibus | 0.002 | <0.001 |
| Less than HS | 0.62 (0.49,0.79) | 0.49 (0.40,0.61) | |
| HS graduate | 0.89 (0.76,1.04) | 0.69 (0.60,0.80) | |
| Some college | 0.92 (0.79,1.07) | 0.81 (0.70,0.93) | |
| Healthcare coverage | Omnibus | 0.14 | <0.001 |
| No | 0.84 (0.66,1.06) | 0.59 (0.48,0.72) | |
| Medical care cost prohibitive | Omnibus | 0.33 | 0.41 |
| Yes | 0.89 (0.72,1.12) | 0.92 (0.76,1.12) | |
| Health status | Omnibus | 0.05 | 0.002 |
| Fair or poor | 1.16 (1.00,1.34) | 1.25 (1.08,1.43) | |
| State | Omnibus | <0.001 | <0.001 |
| CO | 1.50 (1.23,1.82) | 1.04 (0.87,1.24) | |
| DE | 1.12 (0.89,1.41) | 1.73 (1.40,2.13) | |
| DC | 2.00 (1.56,2.58) | 2.28 (1.79,2.90) | |
| MS | 0.88 (0.72,1.07) | 1.14 (0.96,1.35) | |
| RI | 1.72 (1.41,2.09) | 1.71 (1.42,2.06) | |
| SC | 1.11 (0.93,1.34) | 1.56 (1.32,1.84) | |
| WI | 1.10 (0.90,1.35) | 1.45 (1.21,1.74) | |
Numbers shown are odds ratios and 95% confidence intervals, unless otherwise noted. BST = blood stool test, SIG = sigmoidoscopy or colonoscopy
DISCUSSION
This work contributes to a growing body of literature that seeks to understand the complicated relationship between racial discrimination and health. We found that utilization of preventive health services was lower for people who perceived negative racial discrimination while seeking health care than for those who perceived no discrimination. These differences were not statistically significant, however, once other patient characteristics such as race/ethnicity, education, income, and health coverage were controlled. These findings suggest that, although perceived discrimination may be associated with health care utilization, it may not be as important as other factors in guiding patient behavior. For example, we found that patients with lower income or lack of health care coverage were less likely to utilize several of the cancer screenings, suggesting that utilization of these measures are driven by practical concerns such as whether one can afford them (see Appendices A, B and C). We also found that older patients and those with poorer health status were more likely to utilize several of the measures, indicating that health care utilization is driven to a large extent by the health needs of patients.
We also report the novel finding that perceptions of positive discrimination, that is, that one has been treated better than members of other races, was associated with more utilization of most of the preventive measures examined. This is the first study to demonstrate that perceiving race-based preferential treatment is associated with more health care utilization. However, after controlling for patient characteristics, positive discrimination was not a significant predictor of most preventive measures. Given that most existing measures of discrimination do not assess positive discrimination,13,14 the role of positive discrimination in health awaits further research.
The results of previous studies that examined the relationship between perceived discrimination and use of preventive health services are mixed. For instance, Trivedi et al.9 found that perceived discrimination in health care was associated with lower likelihood of obtaining recommended cholesterol testing, A1c tests and foot exams (among patients with diabetes), and of receiving a flu vaccine. Similarly, Blanchard et al.6 found that patients with diabetes, heart disease, or hypertension were less likely to obtain recommended disease-appropriate screenings if they perceived racial discrimination in health care. In contrast, Blanchard et al.6 and Dailey et al.10 both found that there was no relationship between perceived discrimination and obtaining recommended cancer screenings. Trivedi et al.9 also found that perceived discrimination was not associated with PSA testing, nor with aspirin use in adults with high blood pressure or heart disease.
The emerging pattern across studies is that perceived discrimination is related to screenings that are part of managing a chronic disease, but not with receipt of cancer screenings.6,9,10 Our findings are consistent with this, as we found that screenings for breast, cervical, prostate, and colon cancer were unrelated to whether patients perceived negative discrimination in the health care setting, after controlling for patient characteristics.
Our lack of association between negative discrimination and receipt of flu shots is in contrast to one study that found flu shots to be less common among those who perceived discrimination.9 This could be due to differences in the samples utilized in the studies; Trivedi et al.9 used data from California, whereas our study included data from several other states. Although our study represents a broad, multi-state population, its results should be generalized only to the states that contributed data to the analyses.
There are important limitations to consider in interpreting our results. For instance, the data set documents retrospective, self-reported utilization of health services, which may not always be accurate. In addition, the retrospective time frame for some of the preventive measures (e.g., mammogram in past 2 years) exceeded the time frame encompassed by the perceived discrimination item (i.e., past 12 months). This mismatch may explain why perceived discrimination did not predict utilization of the measures in adjusted analyses. The lack of association between discrimination and utilization may also be due to the fact that the BRFSS measures health care discrimination using a single item that assesses only the presence of discrimination rather than the frequency or severity of discriminatory experiences. However, a key strength of this item is that it measured both positive and negative discrimination, whereas existing multi-item validated measures of perceived discrimination focus only on negative discrimination.13–15
In conclusion, we found that there is no statistically significant independent relationship between negative discrimination and the utilization of standard preventive health services, nor is there an independent relationship between positive discrimination and utilization of most services. Future studies exploring the link between perceived discrimination and health outcomes should focus on biological mechanisms2 or other health behaviors that may be shaped by perceived discrimination, such as following medical advice or treatment adherence.
Acknowledgment
Dr. Hausmann was supported by a VA Health Services Research and Development Career Development Award (RCD 06-287). Dr. Ibrahim is the recipient of a VA Health Services Research and Development Award and the Harold Amos Robert Wood Johnson Scholar Award. Dr. Ibrahim is also supported by a K24 Award (1K24AR055259-01) from the National Institutes of Musculoskeletal and Skin Disorders. This publication was also made possible by Grant Number UL1 RR024153 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of NCRR, NIH, or the VA. Information on NCRR is available at http://www.ncrr.nih.gov/. Information on Re-engineering the Clinical Research Enterprise can be obtained from http://nihroadmap.nih.gov/clinicalresearch/overview-translational.asp.
Conflict of Interest None disclosed.
Appendix
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