Patient experience with care is an important dimension of health care quality, and has been shown to predict subsequent health care utilization. For example, higher ratings of care have been found to be associated with lower emergency room use,1 whereas lower satisfaction has been related to a reduced likelihood of compliance with medical regimens among diabetics.2 Prior research has documented the existence of significant racial and ethnic disparities in satisfaction and experiences with care.3–10 Studies using the National Consumer Assessments of Healthcare Providers and Systems (CAHPS) Benchmarking Database have shown that racial/ethnic minorities have worse reports of care than whites in commercial, Medicare, and Medicaid managed care.3–7,9,10
One potential mechanism that may explain the racial/ethnic differences in patient experiences with care is perceived discrimination.11–13 According to the Institute of Medicine, discrimination is differential treatment based on race, ethnicity, sex, or other individual attribute such as health insurance.14 As such, discrimination gives leverage for or against an individual based on that individual’s association with a specific group or class.13,15,16 There is strong evidence that consumers of medical care can experience or perceive discrimination because of one’s health status, insurance status, socioeconomic status, foreign-born status, language spoken at home, or race or ethnicity.11–21 These negative interactions with the health care system may result in worse patient experiences with care.11 The CAHPS reports and ratings of care can provide key insights into the overall quality of care and have been found to be associated with clinical outcomes of care.22
Understanding how discrimination can affect patient experiences is critical to reducing health care disparities and ensuring high quality and culturally competent care. Ngo-Metzger et al17 present a conceptual framework for obtaining the patient’s perspective on culturally competent care. In this framework, health care is experienced by the patient in the context of interactions with providers and other staff within the health care system. The framework classifies these interactions into 6 domains which include: patient-provider communication, respect for patient preferences/shared decision making, experiences leading to trust or distrust, health literacy strategies, access to language services, and experiences of discrimination. The authors argue that there needs to be increased attention to the consequences of discrimination on patient outcomes including satisfaction and experiences with care.
There are a number of studies that examine the relationship between perceived discrimination based on race and patient’s experience with health care.23,24 An analysis of determinants of satisfaction among cardiac patients showed that blacks were more likely to perceive racism and report mistrust of the medical care system, leading to less satisfaction with their health care.18 Another study among diabetics showed that reported experiences of discrimination and racism were associated with reports of problems with medical care.25 A study of low-income blacks found that perceived racism had both a significant, inverse direct effect on satisfaction, as well as a significant indirect effect on satisfaction mediated by cultural mistrust and trust in provider.26 Finally, a more recent examination of the California Health Interview survey found that patients’ perceptions of discrimination based on race/ethnicity were associated with lower ratings of health care.13 Furthermore, perceptions of discrimination fully explained lower ratings of care among blacks.
To our knowledge there are very few studies that examine the prevalence of insurance-based discrimination and its impact on perceptions of care or other outcomes of care. One study of women in Oregon who received prenatal care found that those with lower socioeconomic status were more likely to report insurance-based discrimination. In this study, insurance-based discrimination was associated with fewer breast feeding support actions among these women.24
A specific focus on race/ethnic and insurance discrimination within a Medicaid population is necessary. Medicaid is a large program that enrolls about 60 million Americans27 and provides health insurance coverage for about 27% of all blacks.28 Those on Medicaid are particularly vulnerable to experience or report insurance-based discrimination and/or racial/ethnic discrimination. For example, in the study of women described above, reports of insurance-based discrimination was 3 times more likely among Medicaid beneficiaries.24 Furthermore, Medicaid enrollees appear to be likely to report lower ratings and reports of care compared with commercial enrollees, perhaps because of insurance-related discrimination. In 1 study, commercial health plan enrollees compared with Medicaid beneficiaries rated their plans higher for 4 out of 6 composite measures of health care experiences.29
This study extends the literature by examining the impact of perceived discrimination based on race/ethnicity and insurance status on CAHPS reports and ratings of care among Florida Medicaid beneficiaries. Florida is a large state with substantial enrollment in its Medicaid program and a large proportion of racial/ethnic minorities. In 2007, there were about 1.6 million enrollees under age 65 in Florida Medicaid, representing about 11% of the nonelderly population. Of that number, about 20% were black or African American and 12% were Hispanic.30
CAHPS measures often average 70–90 points on a 0–100 scale and apparently small differences on that scale may correspond to substantial differences in perceptions of care, as reflected in subsequent disenrollment.31 For example, an increase of 5.8 points on the getting needed care composite (on a 0–100 scale) has been associated with halving the rates of voluntary disenrollment from Medicare plans.31,32 We expect a similar or larger effect of perceived discrimination on CAHPS measures.
This is a cross-sectional study that analyzes data from a telephone survey of adult Florida Medicaid beneficiaries, fielded between September and December 2007. The survey is fielded annually at this time on behalf of the Florida Medicaid agency. The survey included the CAHPS Health Plan Survey 4.0, as well as 2 additional items assessing patient experiences with discrimination.
The random sample stratified by plan was drawn from Medicaid administrative data of recipients enrolled in fee-for-service (FFS) and primary care case management, 21 years and older, and who had been in Medicaid for at least 6 consecutive months. Sampled beneficiaries were surveyed by telephone by trained interviewers from the University of Florida Survey Research Center. To maximize response, each telephone number was called up to 25 times, at different times of day, including both weekend and weekday attempts. If a number was disconnected, an additional attempt was made to locate a working phone number through internet searches. The target sample size of 300 completes by plan was based on CAHPS guidelines to ensure adequate plan-level reliability.33 Of those enrollees contacted, 57% completed the survey for a total of 1877 respondents. The respondents included 384 beneficiaries in FFS and 1493 beneficiaries in 4 provider service organizations. The final analytic sample was limited to 1509 respondents (80%) who had a personal doctor, because the CAHPS reports and ratings of care pertain to experiences with personal doctor.
The dependent variables consisted of the CAHPS reports and ratings of care. Reports of care capture-specific experiences with care in terms of what did or did not happen from the consumer’s perspective over the past 6 months. There were 10 items (reports) measuring 4 domains of health plan performance: getting needed care, timeliness of care, communication with doctor, and health plan customer service (see Appendix 1). All items within the 4 domains were administered using a 4-point response scale (never, sometimes, usually, always). The items were transformed linearly to a 0–100 scaled (with a high score representing more favorable perceptions of care), and were then averaged within each composite.
Ratings are personal evaluations of providers and services. As such they reflect both personal experiences as well as the standards used in evaluating care. Four global ratings were asked using a 0 (worse possible) to 10 (best possible) scale. The global ratings were also transformed linearly to a 0–100 scale.
Measures of patient experiences with discrimination are the primary independent variables. Patient experiences with discrimination, based on race/ethnicity and having Medicaid insurance, are assessed by 2 questions which asked: (1) In the last 6 months, how often have you been treated unfairly at this doctor’s office because of your race or ethnicity? and (2) In the last 6 months, how often have you been treated unfairly at this doctor’s office because of the type of health insurance you have or because you do not have health insurance? These items are part of the Equitable Treatment domain of the CAHPS Cultural Competence Item Set.34 Response options were never, sometimes, usually, and always. Each was dichotomized as any discrimination (sometime, usually, or always) versus no discrimination (never).
An additional set of variables known to be related to systematic differences in CAHPS survey responses but not under the control of the plan or provider are used as case-mix adjustors: sex, age, education, and health status.35 Sex is a dichotomous variable: male, female. Age is a categorical variable consisting of 6 levels: 21–24, 25–34, 35–44, 45–54, 55–64, and 65 or older. Education is a categorical variable with 5 levels: 8th grade or less; some high school; high school graduate; some college or 2-year degree; and 4-year college graduate or more. Self-rated health is a categorical variable measuring perceived overall health: excellent, very good, good, fair, and poor. Finally, race/ethnicity (white, Hispanic, black, other), survey language (Spanish and English), and FFS enrollment (1=FFS; 0= not FFS) were included as control variables.
Logistic regressions were used to model the effect of patient demographics (age, sex, education, and race/ethnicity) on the probability of perceived discrimination based on: (1) race/ethnicity, and (2) insurance. Following standard practice for CAHPS data, linear regression (here in the form of generalized linear models) was used to model the effect of patient perceptions of discrimination on CAHPS reports and ratings of care controlling for age, sex, education, self-rated health, race/ethnicity, language survey, and FFS.36 Two separate models were run for each CAHPS outcome measure: (1) perceived discrimination based on race/ethnicity only plus covariates; and (2) perceived discrimination based on Medicaid insurance plus covariates. SEs for all regressions were adjusted for correlation within health plans using the Huber/White correction in SAS Proc GenMod.37
Tables 1 and 2 present descriptive statistics for the dependent and independent variables. Mean CAHPS scores ranged from 72 for getting needed care to 89 for specialist rating. Although 14% of respondents perceived discrimination based on Medicaid insurance, 9% perceived discrimination based on race/ethnicity, and 6% reported both types of discrimination. Approximately 75% of respondents were less than 65 years, 43% had less than high school education, 69% were female, 65% were black or Hispanic, 24% completed a Spanish survey, and 21% were enrolled in FFS. Table 3 shows how perceived discrimination varied by racial/ethnic group. Blacks reported the most discrimination for both Medicaid insurance (19%) and race/ethnicity (12%), whereas whites reported the least discrimination for race/ethnicity (6%) and Hispanics the least discrimination for Medicaid insurance (12%).
Logistic regression results are shown in Table 4. Respondents who were black, middle age (35–64), and those with lower education (8th grade or less) had higher odds of reporting discrimination based on race/ethnicity. In contrast, respondents who were younger than 55 years had higher odds of reporting discrimination based on insurance status.
Case-mix adjusted regression results appear in Table 5. Findings show that Medicaid beneficiaries who reported discrimination based on their race/ethnicity had worse patient experiences than those who did not perceive discrimination. Those reporting discrimination based on race/ethnicity had lower CAHPS scores on all dimensions of care, except timeliness of care, ranging from 15 points lower (on a 0–100 scale) for getting needed care to 6 points lower for specialist rating, compared with those who never experienced discrimination (model 1). The size of these effects ranged from a small to medium effect based on Cohen guidelines in which 0.20 is considered a small effect, 0.50 is a medium effect, and 0.80 or above a large effect.38 The effect size was medium for 2 CAHPS scores (provider communication and health care rating), and small for 5 CAHPS measures (getting needed care, health plan customer service, personal doctor rating, specialist rating, and health plan rating). Those reporting discrimination based on Medicaid insurance had lower scores across all CAHPS measures, ranging from 16 point lower for health plan customer services to 8 points lower for special rating compared with those who never experienced discrimination (model 2). The size of these effects ranged from medium for 5 CAHPS measures (provider communication, health plan customer service, personal doctor rating, health care rating, and health plan rating) to small for 3 CAHPS measures (getting needed care, timeliness of care, and specialist rating).
Although regression residuals were not fully normally distributed, and exhibited the skewness typical of CAHPS data, departures from normality were sufficiently small that the sampling distribution of the SEs of regression coefficients well-approximated normality at these sample sizes, ensuring valid P values.37,39
Understanding the impact of perceived discrimination on patient experience facilitates identification of barriers to health care, the development of strategies to promote positive health care experiences, which can ultimately lead to desirable health outcomes. This study examined the relationship between Medicaid beneficiaries’ reports of provider discrimination and their health care experiences, as measured by CAHPS reports and ratings of care. Study results show that a substantial proportion of beneficiaries reported discrimination on the basis of race/ethnicity (9%) and Medicaid status (14%), with blacks reporting such discrimination most often. Patients who reported discrimination provided substantially lower CAHPS reports and rating of care, with differences as large as 16 percentage points.
There are a number of limitations that are important to note. First, the study used cross-sectional data. Therefore the analysis and conclusions are limited to describing the association between perceptions of discrimination and reports and ratings of care. Unobserved factors may be responsible for the association, as for all observational data. Future longitudinal studies are needed to examine the relationship between perceptions of discrimination and patient experiences with care.23 Second, survey items do not identify specific instances of discrimination, including the nature of the occurrence and as where or when it occurred. Additional qualitative research studies are needed to examine how and why discrimination occurs. For example, focus groups may be conducted to identify practices and behaviors that may be contributing to perceptions of discrimination, and this information can be used in quality improvement activities. Third, because of data limitations we are not able to assess differences in response rate by racial/ethnic group. We had a much higher participation of Hispanics compared with other racial/ethnic groups. This may have been a result of the provider service organizations serving areas with a high concentration of Hispanics, such as Miami-Dade and Broward counties. Finally, the study sample is limited to Florida Medicaid beneficiaries. Although Florida is a racial and ethnically diverse state with a sizeable Medicaid population, readers may want to be cautious in generalizing findings to other states or other groups with other forms of insurance. Nevertheless, the experiences of Florida’s Medicaid population may provide good insight into how beneficiaries in other states may view their medical care.
Results from the study presented here have important implications for practice, policy, and future research aimed at improving experience with care. Findings suggest that reducing perceptions of discrimination may result in improved CAHPS reports and ratings of care. Practices must develop and implement strategies to reduce perceptions of discrimination among patients. Practice behaviors resulting in perceived discrimination range from the very subtle to the most evident. And, as articulated by the framework postulated by Ngo-Metzger et al17 perceived discrimination can result from patient interactions with all types of health care workers including nurses, physicians, office and administrative staff, and other ancillary workers. However, as noted in a recent comprehensive literature review very little research has focused on the specific actions perceived as discriminatory or who in the medical encounter conducted the discriminatory action.23 New research specifically targeted at discovering what patients perceived as discriminatory will aid in the development of strategies that can reduce the incidence of such behaviors.
Cultural competency has been proposed as a broad organizational strategy to ensure effective cross-cultural interactions.25,26 The National Quality Forum (NQF)40 has defined cultural competency as the “ongoing capacity of health care systems, organizations, and professionals to provide for diverse patient populations high-quality care that is safe, patient and family centered, evidence based, and equitable (p. 2).” Furthermore, cultural competency is achieved through “policies, learning processes, and structures by which organizations and individuals develop the attitudes, behaviors, and systems that are needed for effective cross-cultural interactions.”40 Successful implementation of cultural competency requires an organizational commitment toward a systems approach,41,42 and the restructuring of organizational processes to better serve a diverse patient population. The NQF provides a “Comprehensive Framework and Preferred Practices for Measuring and Reporting Cultural Competency,”43 and some of the practices that emerge from this framework relate to: leadership commitment to cultural competency; integration of cultural competency throughout all management practices of the organization; workforce diversity and training; community engagement; patient-provider communication; and care delivery and supporting mechanisms.34 Recent research shows that hospitals that have a higher degree of cultural competency, as assessed by the NQF framework and the Cultural and Linguistic Appropriate Services standards, have higher Hospital CAHPS scores, especially among minority patients.44
As the state and Federal governments increase their efforts toward health plan accountability and public reporting of CAHPS measures, it is imperative that Medicaid health plans use quality improvement efforts to address perceptions of discrimination of their enrolled patient population. In the study state, Florida, policymakers, at the time of the study, were currently experimenting with different forms of managed care within its Medicaid program. To improve cultural competency, contractual arrangements with health plans could include provisions for the assurance of culturally competent care. These policy efforts at a state level could likely lead to the development of unique strategies within the state’s Medicaid delivery system. Such strategies might reduce perceived discrimination in health care among a vulnerable population, a worthy end in itself, and improve the health care experiences of many patients.
APPENDIX 1. CAHPS 4.0 Health Plan Survey Core Composites (Updated December 2007)
1. Gary TL, Maiese EM, Batts-Turner M, et al. Patient satisfaction, preventive services, and emergency room use among African-Americans with type 2 diabetes. Dis Manag. 2005;8:361–371
2. Narayan KM, Gregg EW, Fagot-Campagna A, et al. Relationship between quality of diabetes care and patient satisfaction. J Natl Med Assoc. 2003;95:64–70
3. Weech-Maldonado R, Morales LS, Spritzer K, et al. Racial and ethnic differences in parents’ assessments of pediatric care in Medicaid
managed care. Health Serv Res. 2001;36:575–594
4. Weech-Maldonado R, Morales LS, Elliott M, et al. Race/ethnicity
, language, and patients’ assessments of care in Medicaid
managed care. Health Serv Res. 2003;38:789–808
5. Weech-Maldonado R, Fongwa MN, Gutierrez P, et al. Language and regional differences in evaluations of medicare managed care by Hispanics. Health Serv Res. 2008;43:552–568
6. Weech-Maldonado R, Elliott MN, Morales LS, et al. Health plan effects on patient assessments of Medicaid
managed care among racial/ethnic minorities. J Gen Intern Med. 2004;19:136–145
7. Morales LS, Elliott MN, Weech-Maldonado R, et al. Differences in CAHPS
(R) adult survey reports and ratings by race and ethnicity: an analysis of the national CAHPS
(R) benchmarking data 1.0. Health Serv Res. 2001;36:595–617
8. Wilkins V, Elliott MN, Richardson A, et al. The association between care experiences and parent ratings of care for different racial, ethnic, and language groups in a Medicaid
population. Health Serv Res. 2011;46:821–839
9. Lurie N, Zhan C, Sangl J, et al. Variation in racial and ethnic differences in consumer assesments of health care. Am J Manag Care. 2003;9:502–509
10. Fongwa MN, Cunningham W, Weech-Maldonado R, et al. Reports and ratings of care: black and white Medicare enrollees. J Health Care Poor Underserved. 2008;19:1136–1147
11. Bird ST, Bogart LM. Perceived race-based and socioeconomic status(SES)-based discrimination
in interactions with health care providers. Ethn Dis. 2001;11:554–563
12. Johnson RL, Saha S, Arbelaez JJ, et al. Racial and ethnic differences in patient perceptions of bias and cultural competence in health care. J Gen Intern Med. 2004;19:101–110
13. Sorkin DH, Ngo-Metzger Q, De Alba I. Racial/ethnic discrimination
in health care: impact on perceived quality of care. J Gen Intern Med. 2010;25:390–396
14. Smedley BD, Stith AY, Nelson AR Unequal Treatment. Confronting Racial and Ethnic Disparities in Health Care. 2002 Washington, DC Institute of Medicine of The National Academies Press
15. Gee GC, Ponce N. Associations between racial discrimination
, limited English proficiency, and health-related quality of life among 6 Asian ethnic groups in California. Am J Public Health. 2010;100:888–895
16. Mouton CP, Carter-Nolan PL, Makambi KH, et al. Impact of perceived racial discrimination
on health screening in black women. J Health Care Poor Underserved. 2010;21:287–300
17. Ngo-Metzger Q, Telfair J, Sorkin DH, et al. Cultural Competency and Quality of Care: Obtaining the Patient
. 2006 New York Commonwealth Fund
18. LaVeist TA, Nickerson KJ, Bowie JV. Attitudes about racism, medical mistrust, and satisfaction with care among African American and white cardiac patients. Med Care Res Rev. 2000;57(suppl 1):146–161
19. Bird ST, Bogart LM, Delahanty DL. Health-related correlates of perceived discrimination
in HIV care. AIDS Patient Care STDS. 2004;18:19–26
20. Trivedi AN, Ayanian JZ. Perceived discrimination
and use of preventive health services. J Gen Intern Med. 2006;21:553–558
21. Lillie-Blanton M, Brodie M, Rowland D, et al. Race, ethnicity, and the health care system: public perceptions and experiences. Med Care Res Rev. 2000;57(suppl 1):218–235
23. Shavers VL, Fagan P, Jones D, et al. The state of research on racial/ethnic discrimination
in the receipt of health care. Am J Public Health. 2012;102:953–966
24. Thorburn S, De Marco M. Insurance-based discrimination
during prenatal care, labor, and delivery: perceptions of Oregon mothers. Matern Child Health J. 2010;14:875–885
25. Hausmann LR, Kressin NR, Hanusa BH, et al. Perceived racial discrimination
in health care and its association with patients’ healthcare experiences: does the measure matter? Ethn Dis. 2010;20:40–47
26. Benkert R, Peters RM, Clark R, et al. Effects of perceived racism, cultural mistrust and trust in providers on satisfaction with care. J Natl Med Assoc. 2006;98:1532–1540
27. The Henry J. Kaiser Family Foundation. Kaiser commission on Medicaid
and the uninsured. Medicaid Matters: Understanding Medicaid
’s Role in Our Health Care System
. 2011. Available at: http://www.kff.org/medicaid/upload/8165.pdf
. Accessed June 12, 2012
28. The Henry J. Kaiser Family Foundation. The Kaiser commission on Medicaid
and the uninsured. Medicaid
’s Role for Black Americans
. 2011. Available at: http://www.kff.org/medicaid/upload/8188.pdf
. Accessed June 12, 2012
29. Elliott MN, Farley D, Hambarsoomians K, et al. Do Medicaid
and commercial CAHPS
scores correlate within plans?: A New Jersey case study. Med Care. 2005;43:1027–1033
30. Henry J. Kaiser Family Foundation. Medicaid
coverage rates for the nonelderly by race/ethncity, states (2007–2008), U.S (2008), Florida. Available at: http://www.statehealthfacts.kff.org
. Accessed September 9, 2010
31. Elliott MN, Haviland AM, Dembosky JW, et al. Are there differences in the Medicare experiences of beneficiaries in Puerto Rico compared with those in the U.S. mainland? Med Care. 2012;50:243–248
32. Bender R, Guess L, Trang L. Beneficiary reported experience and voluntary disenrollment in Medicare managed care. Health Care Financ Rev. 2003;25:55–66
34. Weech-Maldonado R, Dreachslin JL, Brown J, et al. Cultural competency assessment tool for hospitals: evaluating hospitals’ adherence to the culturally and linguistically appropriate services standards. Health Care Manage Rev. 2012;37:54–66
35. Elliott MN, Swartz R, Adams J, et al. Case-mix adjustment of the National CAHPS
benchmarking data 1.0: a violation of model assumptions? Health Serv Res. 2001;36:555–573
36. Landon BE, Zaslavsky AM, Bernard SL, et al. Comparison of performance of traditional Medicare vs Medicare managed care. JAMA. 2004;291:1744–1752
37. White H. A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica. 1980;48:817–830
38. Cohen J Statistical Power Analysis for the Behavioral Sciences. 1988 Hillsdale, NJ Lawrence Erlbaum Associates
39. Chen L. Testing the mean of skewed distributions. J Am Stat Assoc. 1995;90:767–772
40. Endorsing a Framework and Preferred Practices for Measuring and Reporting Culturally Competent Care Quality. 2008 Washington, DC National Quality Forum
41. Curtis EF, Dreachslin JL, Sinioris M. Diversity and cultural competency training in health care organizations: hallmarks of success. Health Care Manag. 2007;26:255–262
42. Dreachslin JL, Myers VL. A systems approach to culturally and linguistically competent care. J Healthc Manag. 2007;42:220–226
43. A Comprehensive Framework and Preferred Practices for Measuring and Reporting Cultural Competency. 2008 Washington, DC National Quality Forum
44. Weech-Maldonado R, Carle AC, Weidmer B, et al. The Consumer Assessment of Healthcare Providers and Systems (CAHPS
) Cultural Competence (CC) item set. Med Care
2012;50(suppl 2): S22–S31