peer-reviewed article regarding health disparities and/or the social determinants of health.
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Perceived_discrimination_in_me.pdf
RESEARCH ARTICLE
Perceived discrimination in medical settings
and perceived quality of care: A population-
based study in Chicago
Maureen R. BenjaminsID 1,2*, Megan Middleton2
1 Sinai Urban Health Institute, Sinai Health System, Chicago, Illinois, United States of America, 2 Chicago
Medical School, Rosalind Franklin University of Medicine and Science, North Chicago, Illinois, United States
of America
Abstract
Perceived discrimination in medical settings remains prevalent within the U.S. health care
system. However, the details of these experiences and their associations with perceived
quality of care are not well understood. Our study assessed multiple measures of perceived
racial/ethnic discrimination in medical settings and investigated the locations and purported
perpetrators of the discriminatory experiences within a population-based sample of 1,543
Black, White, Mexican, Puerto Rican, and Other adults. We used logistic regression to esti-
mate associations between perceived discrimination in the medical setting and three quality
of care indicators. Overall, 40% of the sample reported one or more types of perceived dis-
crimination in a medical setting, with significant differences by race/ethnicity. Discrimination
was perceived across health settings and from a variety of providers and staff. In adjusted
logistic regression models, individuals reporting discrimination had more than twice the
odds of reporting fair or poor quality of care (OR = 2.4 [95% CI: 1.4–4.3]). In addition, per-
ceived discrimination in medical settings was significantly associated with report of not hav-
ing enough time with the physician and not being as involved in decision-making as desired.
These findings expand our understanding of perceived discriminatory experiences in health
care and the consequences of it for patients, providers, and health care systems. This infor-
mation is essential for identifying future provider interventions and improving the training of
health care professionals.
Introduction
Racial and ethnic disparities in access to, and quality of, health care are pervasive and contrib-
ute to the persistent negative health outcomes seen among communities of color [1–7]. Per-
ceived discrimination may underlie both disparities in health care and health outcomes [8,9].
In particular, research is needed to better understand racial and ethnic discrimination in the
health care setting, which likely impacts health care perceptions and outcomes [10–13].
PLOS ONE | https://doi.org/10.1371/journal.pone.0215976 April 25, 2019 1 / 15
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Citation: Benjamins MR, Middleton M (2019)
Perceived discrimination in medical settings and
perceived quality of care: A population-based study
in Chicago. PLoS ONE 14(4): e0215976. https://
doi.org/10.1371/journal.pone.0215976
Editor: Leonidas G Koniaris, Indiana University,
UNITED STATES
Received: November 14, 2018
Accepted: April 11, 2019
Published: April 25, 2019
Copyright: © 2019 Benjamins, Middleton. This is an open access article distributed under the terms
of the Creative Commons Attribution License,
which permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All data underlying
the findings reported in the submitted manuscript
are publicly available through the Inter-university
Consortium for Political and Social Research (Sinai
Community Health Survey 2.0, Chicago, Illinois,
2015-2016 (ICPSR 37073)).
Funding: The Sinai Community Health Survey 2.0
was funded by The Chicago Community Trust
(www.cct.org), grants C2013-00630, C2014-
01723, and C2015-04294. The funders had no role
in the design of the current study, data collection
Patient perceptions of quality are important to study because there is a growing literature
linking them with health care outcomes [14–15]. Perceptions of quality are now being incor-
porated into value-based incentive payments from the government and other organizations, as
well as health care provider ratings [16]. Health care providers also rely on patient reports of
quality to guide continuous quality improvement efforts. Given the increasing significance of
perceived quality of care, more research is needed to understand the factors associated with it.
Despite this, only a handful of studies have examined the association between discrimina-
tion in health care and quality of care ratings, with most confirming the expected negative rela-
tionship [17–20]. More broadly, previous studies have found that perceiving discrimination
in a medical setting is associated with other health care outcomes, such as delayed or unmet
health care needs [20–23], underutilization of mental health services [24], and increased emer-
gency department visits and hospital admissions [12]. However, the literature on discrimina-
tion in medical settings has been limited by measurement issues and unrepresentative samples
[13]. For example, previous studies have commonly used a single question to assess whether or
not an individual has perceived discrimination while receiving health care [10]. In addition,
the majority of studies in this area focus on African American populations, with limited inves-
tigation into discrimination among other groups of color and between racial/ethnic popula-
tions typically combined into one group (e.g., Hispanics) [10, 13, 25].
Furthermore, there is a dearth of information about the purported perpetrators and settings
of the discriminatory event [10]. One study, focusing on discrimination due to HIV status,
assessed the perpetrators and found attributions spread among clinical staff (more than
case managers or social workers) [26]. Another study examined the location of perceived dis-
criminatory health care experiences and revealed that individuals using community clinics
rather than doctor’s offices as their source of primary care reported higher rates of discrimina-
tion [27]. However, this finding was true only for the middle socioeconomic subgroup of
participants.
To address these gaps in the literature, our study investigates the association of perceived
discrimination in medical settings with three measures of perceived quality of care within a
population-based sample from selected Chicago communities. Importantly, this sample
includes sufficient data to examine four racial/ethnic groups (Non-Hispanic Black, Mexican,
Puerto Rican, and Non-Hispanic White) and uses multiple measures of perceived discrimina-
tion, including a 7-item scale of discrimination in medical settings and questions that ask
about discrimination due to insurance status and English proficiency. Finally, we also examine
the purported perpetrators and settings of perceived discriminatory events. This new informa-
tion can be used to inform the training of health care professionals and the development of
policies within health care organizations to reduce perceived discrimination, with the goals of
improved patient experience and greater health equity.
Methods
Sample
Our analysis used data from the Sinai Community Health Survey 2.0 (Sinai Survey 2.0).
Detailed information on the sampling design and data collection methodology is available else-
where (www.sinaisurvey.org). To summarize, the Sinai Survey 2.0 was administered by trained
interviewers from the University of Illinois at Chicago (UIC) Survey Research Laboratory
between March 2015 and September 2016. The sample was randomly selected from ten Chi-
cago community areas. The communities were chosen based on geographic location and
racial/ethnic composition, representing some of the most socially and economically challenged
neighborhoods in Chicago. The sampled area represented approximately 386,000 individuals.
Perceived discrimination in medical settings and quality of care
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and analysis, decision to publish, or preparation of
the manuscript.
Competing interests: The authors have declared
that no competing interests exist.
The community areas were divided into primary sampling units (PSU). The PSUs, and
households within them, were randomly selected using Probability Proportionate to Size
methodology. Selected households were mailed an advance letter with study information
before the first contact. Following this, one or two adult(s) (18 years or older) were randomly
selected from each household. An extensive protocol was followed to maximize the number of
interviews completed, including up to ten in-person contact attempts, up to five telephone
attempts, and materials left at the door.
Interviews were conducted face-to-face, in English or Spanish (depending on respondent
preference) using computer-assisted personal interviewing software. The overall response rate,
which includes some households with unknown eligibility, was 28.4% (calculated with Ameri-
can Association of Public Opinion Research’s (AAPOR) response rate number 3) [28]. The
cooperation rate, or the proportion of respondents who completed an interview after contact,
was 53.9% (AAPOR, response rate 4). The final sample included 1,543 adults. The Sinai Survey
2.0 was approved by the IRBs of the University of Illinois at Chicago (#2014–0524) and Mount
Sinai Hospital (MSH #14–17). Interviewers explained the study to all participants, who then
had the opportunity to ask questions before signing the informed consent document. The
dataset and questionnaires are available through the Inter-university Consortium for Political
and Social Research website (Sinai Community Health Survey 2.0, Chicago, Illinois, 2015–
2016 (ICPSR 37073)).
Measures
Health Care Utilization. Our dependent variable, perceived quality of care, was measured with the following question: “Overall, how would you rate the quality of health care you received in
the last 12 months? Would you say excellent, very good, good, fair, or poor?” Those reporting
fair or poor care were dichotomized from those reporting excellent, very good, or good care.
Two other, more specific, indicators of quality of care were also asked. These were slightly
modified from the Commonwealth Fund Health Care Survey (2001) and reflect items from
the Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey related to cli-
nician communication [29]. Both were prefaced with the instruction to think about one’s last
visit to a doctor. The questions were: “How much did the doctor involve you in decisions
about your care?” and “How much time did the doctor spend with you?” For both, respon-
dents were given the following response options: “as much as you wanted, almost as much as
you wanted, less than you wanted, or a lot less than you wanted.” The responses were dichoto-
mized into positive and negative categories.
Discrimination in Medical Settings. For the primary independent variable, we used a slightly modified version of the Discrimination in Medical Settings scale (DMS) [12, 19, 30, 31], which
is based on the Everyday Discrimination Scale (EDS) [32]. Questions were prefaced with the
following: “Please think about all the times in your life when you’ve gotten health care. When
getting health care, how often have any of the following things happened to you because of
your race, ethnicity, or color?” During the questionnaire development, there was interest from
several researchers in adding an item about providers acting as if they were unwilling to touch
the patient, based on conversations with community members. Given the limited space avail-
able, the difficult decision was made to make room for this item by substituting it for another
item from the scale. Because the item on being treated with less courtesy was perceived to over-
lap the most with the remaining items, it was excluded. The response scale for all items was
never, rarely, sometimes, or often. Preliminary analyses showed that the responses had highly
skewed distributions for each question, with 74–94% of responses falling in the “never”
Perceived discrimination in medical settings and quality of care
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category. Thus, the responses were dichotomized to represent never experienced discrimina-
tion vs. ever (as done in previous uses of the scale) [12, 19].
For those reporting any lifetime experience of perceived discrimination in a medical setting
(based on an affirmative answer to one or more of the DMS items), as well as a health care visit
in the past 12 months, we asked about the individual involved and the location of the most
recent time they perceived this type of discrimination. To identify the purported perpetrator,
we asked, “Was the person who treated you this way your doctor, a nurse, a receptionist, or
someone else?” Respondents could choose all that apply. The location measure assessed
whether this most recent event took place in a doctor’s office, an emergency room, a clinic, or
somewhere else. Respondents could only identify one location.
Other measures of perceived discrimination in medical settings included a question that
assessed whether respondents felt that they had been “judged unfairly” or “treated with disre-
spect” by the doctor or medical staff due to their race, ethnicity, or color in the past 12 months
using a four-point Likert-like scale ranging from 1 (never) to 4 (often). Perceived discrimina-
tion based on insurance-status and English proficiency was also assessed. Respondents were
asked to think about their experiences in health care in the last 12 months and answer yes or
no to the following questions: “Have you felt that the doctor or medical staff you saw judged
you unfairly or treated you with disrespect because of the type or health insurance you have, or
your ability to pay for care?” and “. . .because of how well you speak English?” These questions
were only asked for those with a health care visit in the past 12 months.
Demographic and Socioeconomic Characteristics. Demographic variables included age, gen- der, and race/ethnicity (non-Hispanic White, non-Hispanic Black, Mexican, and Puerto
Rican). Members of other racial/ethnic groups (including Hispanic and non-Hispanic individ-
uals) were not examined in stratified analyses due to small sample sizes. Socioeconomic vari-
ables included education, employment, and current health insurance. Unmet health care
needs measured whether or not respondents had health care needs in the past year that they
did not receive due to cost. Health care needs included: medical care or surgery; a doctor’s
appointment; prescription medicine; mental health care or counseling; dental care; and/or,
eyeglasses.
Other Covariates. Global discrimination measured personal experiences of perceived dis- crimination due to race, ethnicity, or color using a four-point scale ranging from 1 (never) to 4
(often). These responses were dichotomized to reflect whether or not the participants had ever
experienced discrimination. Self-rated health was assessed by asking: “Would you say that in
general your health is excellent, very good, good, fair, or poor?” This variable was dichoto-
mized into excellent, good, or very good health versus fair or poor health.
Data analyses
We first generated descriptive statistics for the total sample and for the largest four racial/eth-
nic groups. Next, we examined bivariate relationships between our primary discrimination in
medical settings outcome (DMS) and the three quality variables. Multivariate logistic regres-
sion models were also used to assess these associations, controlling for demographic, socioeco-
nomic, unmet health care needs, and other covariates. For each of the three outcomes, both
unadjusted and adjusted models were run. We also ran models with interaction terms between
race/ethnicity and discrimination in health care to explore effect modification.
The survey team also conducted a nonresponse bias analysis to better understand potential
bias due to the low response rate and sample selection (data not shown). Briefly, systematic
block and housing unit observations were added to the data, along with block-group level data
from the Census Bureau’s American Community Survey. Models were then run to identify
Perceived discrimination in medical settings and quality of care
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variables that independently predicted the odds of 1) the primary respondent completing an
interview and 2) having poor health outcomes or risk factors (as assessed by at least one nega-
tive response to 16 diverse health-related questions). Finally, any identified variables were used
to re-estimate nonresponse-adjusted weights to account for potential nonresponse bias and
estimates for each health indicator were compared with those using the previously estimated
standard weights (which adjusted for gender, age, and race/ethnicity).
Statistical significance was set at p<0.05. All analyses were conducted in Stata 14.2 and
account for the complex survey design. Estimates are also weighted to be representative of the
entire population from which the sample was drawn.
Results
Descriptive statistics
Demographic and socioeconomic characteristics. Sample characteristics are shown in
Table 1 for the full sample and by racial/ethnic group. The majority of the sample identified as
a racial or ethnic minority. Survey respondents were evenly split between sexes and the mean
age was 42 years. Approximately three-fourths of the sample had at least a high school degree
and the vast majority were employed. Both Whites and Blacks had a significantly higher high
school graduation rate than Mexicans, while Blacks were more likely to be unemployed than
Whites or Puerto Ricans. Twenty-one percent of respondents were uninsured and one-third
had unmet health care needs due to cost in the past year. White and Black adults were less
likely to be uninsured than Hispanics; Blacks and Mexicans had higher rates of unmet health
needs than Whites. Almost two-thirds of respondents had ever perceived discrimination in
general. Whites were significantly less likely to report this than Blacks and Mexicans. Finally,
one-third reported fair or poor health.
Health care outcomes. Fifteen percent reported receiving fair or poor quality health care
in the past year. This number was significantly lower for White respondents compared to
Blacks and Mexicans. Seven percent reported that they were involved in decisions less than
they wanted and 15% had less time with the doctor than they wanted. These numbers did not
vary significantly by race/ethnicity.
Discrimination in medical settings. Overall, 40% had ever experienced some type of
discrimination in a medical setting (DMS) (Table 2). This differed significantly by race/eth-
nicity, with Whites being less likely to report discrimination than the three groups of color
and Mexicans being less likely to report it than Blacks. The scale item “received poorer ser-
vice” was most frequently reported (29%). Again, significant racial/ethnic differences exist.
For example, only 3% of Whites reported experiencing this type of discriminatory event,
compared to 43% of Blacks. The scale item “. . .doctor or nurse acts as if he or she is afraid of
you” had the lowest overall affirmation rate (6%); however, among Blacks, 14% perceived
this type of discrimination.
Overall, a smaller percentage reported discrimination in a medical setting when it was
asked as a single question (separate from the DMS scale) and limited to experiences in the past
year. For example, only 18% reported any level of perceived discrimination in a medical setting
when asked in this manner. Affirmative responses ranged from no Whites reporting this to
one-quarter of Mexicans. Very few responded that this type of discrimination occurred
“often”.
Purported Perpetrator. Those who responded affirmatively to any of the DMS items and had a health care visit in the past year were asked to identify the perpetrator(s) of the most
recent time they perceived being discriminated against. A substantial percentage selected each
of the four potential options (i.e. doctor, nurse, receptionist, or someone else). The only racial/
Perceived discrimination in medical settings and quality of care
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ethnic difference was that Whites were significantly less likely to report perceived discrimina-
tion from a receptionist compared to Mexicans.
Location. Similar to above, respondents who reported any type of perceived discrimination in the DMS and who had a health care visit in the past year were asked about the location of
the most recent discriminatory event. Responses were evenly distributed between the four
options of a doctor’s office, the emergency room, a clinic, and elsewhere. Whites were less
likely to report such experiences in a clinic setting compared to the other groups, but no
racial/ethnic differences were seen.
Judged Unfairly. Overall, 13% of those with a health care visit in the past year reported that they had been judged or treated unfairly by a doctor or staff member because of their type of
insurance or ability to pay. Blacks were significantly more likely to report this than Whites and
Mexicans. Overall, only 2% reported being treated unfairly due to how well they spoke English.
Whites were significantly less likely to report this type of perceived discrimination compared
to other groups.
Bivariate analyses
Fig 1 displays results from the bivariate analyses. Those reporting DMS were more than twice
as likely to rate their quality of care as fair or poor compared to those with no DMS (24% [95%
CI: 18–30%] versus 9% [95% CI: 6–13%], respectively). Those reporting DMS were also signifi-
cantly more likely to be less involved in decisions than they wanted (11% [95% CI: 8–15%])
Table 1. Demographic, health, and health care characteristics by race/ethnicity a .
Total NH White NH Black Mexican Puerto Rican
Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI)
Demographics Male 50 (46–54) 54 (43–65) 45 (40–50) 54 (49–60) 49 (38–59)
Age (mean) 42 (40–44) 47 (44–50) 42 (39–45) 39 (37–41) 45 (41–49)
English as primary language 86 (81–89) 100 b
100 b
70 (62–77) 89 (74–96)
Married 38 (33–42) 51 (39–63) 20 (15–27) 45 (38–52) 34 (23–46)
Socioeconomic Status High school degree or more 73 (68–78) 99 (97–100) 78 (71–84) 62 (52–70) 68 (51–81)
Unemployed 10 (8–12) 3 (1–8) 16 (11–21) 8 (5–12) 4 (2–9)
Access to Care Health insurance 79 (75–83) 93 (87–97) 89 (84–93) 66 (58–73) 66 (58–73)
Any unmet health care needs 33 (29–38) 19 (12–27) 42 (35–49) 32 (35–49) 33 (22–47)
General Discrimination Any discrimination 64 (59–69) 37 (26–48) 73 (66–79) 67 (60–74) 63 (47–76)
Self-Rated Health Fair or poor 33 (29–37) 18 (10–28) 34 (26–43) 37 (31–42) 31 (20–45)
Health Care Quality Outcomes Perceived quality of care as fair/poor 15 (12–19) 3 (1–6) 16 (12–22) 20 (14–28) 11 (5–25)
Not involved in decisions 7 (5–9) 8 (5–14) 6 (4–9) 8 (5–13) 5 (2–12)
Little time with doctor 15 (12–19) 10 (6–17) 15 (10–22) 17 (12–25) 18 (10–32)
N 1,543 c 219 536 521 151
Notes: NH = non-Hispanic; CI = confidence interval a Sinai Community Health Survey 2.0 (2015–2016, ten Community Areas in Chicago, IL). All statistics weighted for clustered survey sampling design. b
No confidence interval. c
Total sample includes individuals in racial/ethnic groups other than those displayed separately.
https://doi.org/10.1371/journal.pone.0215976.t001
Perceived discrimination in medical settings and quality of care
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versus 4% [95% CI: 3–7%], respectively)) and have less time with the doctor than they wanted
compared to those reporting no DMS (21% [95% CI: 17–27%]) versus 10% [95% CI:7–16%],
respectively).
Logistic regression analyses
We report unadjusted and adjusted odds ratios in Table 3. The findings from the six logistic
regression models indicate that DMS is significantly associated with all three quality of care
outcomes (i.e. overall perceptions of health care quality as fair or poor, less involvement in
health care decisions than desired, and less time spent with one’s physician than desired). In
Table 2. Perceived discrimination in medical settings and related factors by race/ethnicity, Sinai Community Health Survey 2.0 (2015–2016, ten Community Areas in Chicago, IL)
a .
Overall NH White NH Black Mexican Puerto Rican
Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI)
Discrimination in Medical Settings (ever)
Any Type of Discrimination in Medical Settings 40 (35–45) 13 (8–20) 56 (48–63) 39 (32–46) 44 (31–58) Doctor or nurse is not listening to you 24 (20–28) 4 (2–11) 34 (29–41) 23 (18–30) 28 (16–43)
Treated with less respect 25 (20–29) 3 (1–9) 34 (27–42) 25 (19–31) 29 (17–44)
Received poorer service 29 (24–34) 3 (1–10) 43 (35–51) 28 (22–34) 33 (21–48)
Doctor or nurse acts better than you 18 (15–22) 7 (4–11) 26 (20–32) 15 (10–20) 23 (13–39)
Doctor or nurse acts as if you are not smart 18 (14–22) 7 (3–13) 29 (23–36) 14 (10–19) 26 (14–42)
Doctor or nurse acts as if he or she is afraid of you 6 (4–9) - - b
14 (10–21) 4 (2–7) 5 (2–11)
Doctor or nurse did not want to touch you 8 (6–10) - - b
14 (11–19) 6 (4–10) 5 (2–11)
Treated Unfairly When Getting Medical Care (past year) c
Never 82 (77–85) 100 (98–100) 80 (73–85) 76 (68–83) 85 (69–93)
Rarely 11 (8–15) - - b
10 (7–15) 17 (11–24) 8 (2–22)
Sometimes 6 (4–9) - - b
8 (5–14) 6 (3–11) 7 (2–23)
Often 1 (0–3) - - b
2 (1–4) 2 (1–4) - - b
Purported Perpetrator of Most Recent Discriminatory Event de
Doctor 25 (19–33) 29 (10–58) 30 (19–45) 22 (13–36) 16 (7–31)
Nurse 30 (24–36) 21 (7–48) 31 (23–41) 24 (17–34) 39 (19–63)
Receptionist 23 (17–29) 7 (3–19) 18 (10–30) 29 (22–37) 26 (11–51)
Someone else 22 (17–28) - - b
25 (18–34) 23 (16–33) 13 (6–27)
Location of Most Recent Discriminatory Event e
Doctor’s office 29 (22–36) 19 (8–37) 33 (22–48) 25 (15–38) 34 (18–55)
Emergency room 30 (23–38) 44 (19–73) 32 (20–47) 31 (22–41) 28 (12–52)
A clinic 20 (15–25) - - b
19 (13–28) 18 (12–28) 17 (7–36)
Somewhere else 22 (17–28) 31 (12–60) 16 (10–24) 26 (18–37) 21 (7–50)
Judged or Treated Unfairly by Doctor or Staff c
Because of type of insurance or ability to pay 13 (11–17) 7 (4–12) 22 (16–29) 10 (6–15) 15 (7–32)
Because of how well you speak English 2 (0–8) - - b
4 (2–7) 11 (7–15) 5 (2–13)
N 1,543 219 536 521 151
Notes: NH = non-Hispanic; CI = confidence interval a
All statistics weighted for clustered survey sampling design. b
Insufficient cell size (n<5). c
Limited to those with a health care visit in past 12 months. d
Respondents could choose more than one answer. e
Limited to those with a health care visit in past 12 months and who reported a discriminatory event.
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the three unadjusted models, individuals who report any perceived discrimination in a medical
setting have two to three times higher odds of reporting each of the negative health care quality
outcomes.
In the three adjusted models, two of the odds ratios are slightly attenuated, but all remain
significant. Specifically, individuals reporting perceived discrimination in a medical setting
had more than twice the odds of reporting fair or poor quality of care (OR = 2.4 [95% CI: 1.4–
4.3]). Perceived discrimination in medical settings was also significantly associated with not
Fig 1. Three measures of health care quality by lifetime experience of perceived discrimination in medical settings ab
. a Sinai
Community Health Survey 2.0 (2015–2016, ten Community Areas in Chicago, IL). All statistics weighted for clustered survey sampling design.
b “Any Perceived Discrimination in Medical Settings” indicates an affirmative response to any item in the
Discrimination in Medical Setting scale.
https://doi.org/10.1371/journal.pone.0215976.g001
Table 3. Unadjusted and adjusted odd ratios for the association of perceived discrimination in medical settings with three health care quality outcomes a .
Perceived Quality of Care (Fair/Poor) Not Involved in Decisions Little Time with Doctor
OR (95% CI) OR (95% CI) OR (95% CI)
Discrimination in Medical Settings
Unadjusted Models 3.2 (1.9–5.3) 2.9 (1.6–5.2) 2.4 (1.4–4.2)
n = 1,397 n = 1,529 n = 1,530 Adjusted Models
b 2.4 (1.4–4.3) 2.4 (1.3–4.4) 2.6 (1.5–4.6)
n = 1,243 n = 1,362 n = 1,364
Notes: a Sinai Community Health Survey 2.0 (2015–2016, ten Community Areas in Chicago, IL). All statistics weighted for clustered survey sampling design. b
Adjusted for age, sex, race/ethnicity, marital status, education, employment, insurance, unmet health care needs, general discrimination, and self-rated health.
Excludes members of Other race/ethnic category.
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being as involved in decision-making as desired (OR = 2.4 [95% CI: 1.3–4.4]) and not having
enough time with the physician (OR = 2.6 [95% CI: 1.5–4.6]).
Results from models including the interaction terms between race/ethnicity and discrimi-
nation in health care (not shown) suggested that effect modification was likely for two of the
three quality outcomes (perceived quality of care and involvement in decisions). In these mod-
els, discrimination in health care was most strongly associated with the quality outcomes for
Blacks and Mexicans. However, the small sample sizes precluded stratifying models by race/
ethnicity.
Nonresponse bias
In the nonresponse bias analyses (not shown), two variables—concentrated economic disad-
vantage (percent unemployed, percent female-headed families with children, percent Black,
and percent below the poverty level) and concentrated immigration (percent Hispanic and
percent foreign-born)—were associated with both nonresponse and at least one of the 16
selected health measures. When comparing estimates for each health indicator using the stan-
dard weights and the nonresponse-adjusted weights, all estimates were similar (i.e. none of the
nonresponse-adjusted health indicator estimates fell outside the 95% confidence intervals of
the standard weighted estimates).
Discussion
A positive patient experience is increasingly recognized as an essential element of high quality
health care [33]. Accordingly, perceptions of quality of care are now included in determina-
tions of governmental funding and provider ratings. Emerging literature has found that per-
ceptions of low-quality care may be linked to poorer health care outcomes (such as delayed
care and non-compliance with treatment) as well as objective measures of quality of care [14,
22]. However, little is known about the predictors of patient quality ratings. Our study adds
to the evidence by exploring how frequently perceived discrimination in medical settings is
reported, who is allegedly perpetrating it, where it happens, and how it is associated with per-
ceived quality measures.
Overall, 40% of adults in this sample responded affirmatively to one or more items on the
DMS, with significant differences by race/ethnicity. Receiving poorer service was the most fre-
quently reported issue, with over 40% of Blacks reporting this type of discriminatory event.
Few patterns were seen regarding the purported perpetrators and locations identified. More
specifically, doctors, nurses, receptionists, and others were all sources of perceived discrimina-
tion. Similarly, substantial percentages of the population reported perceived discriminatory
events at each type of clinical location. Finally, in adjusted models, reporting one or more
types of discrimination in a medical setting was significantly associated with reporting fair or
poor quality of care, not having enough time with the physician, and not being as involved in
decision-making as desired.
Comparison with previous findings
Previous studies using the DMS scale reflect a wide range of prevalence rates, from 8% of
female veterans [34] to over 60% of those included in a convenience sample of African Ameri-
can adults in northern Ohio [12] and a sample of HIV patients [29]. Consistent with the cur-
rent literature, we found that the perception of race-related fear from doctors or nurses toward
patients was the least reported type of perceived discrimination [12, 30, 34, 35]. In previous
studies, perceiving that providers were “not listening” was the most commonly reported item
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on the DMS [12, 19, 29, 30, 34]; however, in our study, receiving “poorer services” was most
frequently reported.
Not surprisingly, our study found lower levels of perceived discrimination in health care
(18%) when using a single-item measure and when limiting events to the past 12 months.
Many previous cross-sectional studies on general populations (also using single-item question)
have reported far lower rates of health care discrimination, ranging from 1% to 9%, compared
to studies using the DMS [17, 22, 24, 36–44]. Most of these had predominantly White sample
populations [22, 24, 36–39]. In contrast, a cross-sectional study conducted in Chicago in 2002
yielded a higher prevalence of 22% [20].
Consistent with much of the previous literature, our study found that Blacks reported the
highest rates of health care discrimination (56%) using the DMS scale [10, 45, 39, 43, 44]; how-
ever, rates among Puerto Ricans and Mexicans far exceeded previous findings at 45% and
40%, respectively. Few studies have estimated prevalence rates within the large and diverse
Latino population [17, 41]. One study of Puerto Ricans in Boston found that 12% had experi-
enced discrimination in medical settings [46]. Another found nearly equal rates of perceived
healthcare discrimination between adults of Mexican and Puerto Rican descent, at roughly
24% [20].
Perceived discrimination and perceived quality of health care
The current study found that DMS is associated with three measures of quality of care (related
to overall perceived quality, involvement with decisions, and time spent with physician), in
line with the existing studies. For example, one study found that perceiving discrimination
while receiving health care was the primary predictor of the variance in quality of care ratings
between Black and White patients [17], while another found that perceived discrimination in
health care (not necessarily due to race/ethnicity) was related to perceived quality of care for
foreign-born (but not U.S. born) Hispanics [18]. Most existing studies on perceived discrimi-
nation in health care and quality outcomes have used single item discrimination measures [17,
18, 30, 43, 47]. As an exception, a study using a small sample of Black and White veterans
found that a multi-item scale of discrimination in health care was associated with quality of
diabetes care [19].
Strengths and limitations
The present research builds upon the literature by examining the prevalence of this type of dis-
crimination for adults of Mexican and Puerto Rican descent, which addresses recent calls to
add to the limited body of health care discrimination research on these growing populations
[25, 27, 41]. In addition, we were able to enlist the more detailed DMS tool in order to attain
more actionable and specific data regarding perceived discriminatory experiences in health
care settings. This study is also among the first to assess the locations and purported perpetra-
tors of perceived discrimination in health care. It is critical to understand that the patient expe-
rience, and perceptions of quality, are impacted at all stages of the clinical process, from ease of
scheduling to interactions with office staff (who are often a patient’s first point of contact), to
physician encounters [48]. By studying the purported perpetrators and locations reported in
the context of discriminatory events, we are able to more clearly understand the patient experi-
ence and, consequently, collectively work to improve patient care and health outcomes
through targeted interventions.
It should be noted that these data, which were collected using a probability sample of ten
diverse Chicago communities, do not represent greater Chicago or U.S. populations. As dis-
cussed above, the overall response rate was low (28.4%, AAPOR response rate type 3) [28]. We
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weighted all statistics to make the results representative of the sampling frame to account for
this. Moreover, the cooperation rate, which only includes those individuals with whom inter-
viewers made contact, was almost double (53.9%, AAPOR cooperation rate type 4) [28]. These
rates reflect the general decline in response rates seen nationally. As with all surveys, we must
consider whether participants differ from non-participants in characteristics related to our
variables of interest (or the relationships between them). Our nonresponse bias analysis did
not show evidence of this type of bias in these data. However, we were unable to specifically
test for differences in levels of perceived discrimination or healthcare satisfaction between
responders and nonresponders. One might hypothesize that individuals with higher levels of
perceived discrimination in medical settings and lower levels of healthcare satisfaction would
be less likely to participate than other individuals, particularly given that our survey was con-
ducted by a research center that is part of a healthcare system. If this was the case, our numbers
underestimate the extent of perceived discrimination in our healthcare system, while overesti-
mating levels of satisfaction with care.
Another of our study’s weaknesses is intrinsic to the measure of perceived discrimination.
Self-reported discrimination measures reflect only what subjects are able to identify and recall,
and willing to report. Moreover, several measures related to discrimination in a medical setting
were limited to those who reported a health care visit in the past year. The use of odds ratios as
a measure of association may overstate the association, given that both the outcome and expo-
sure are prevalent. Finally, the cross-sectional nature of the data precluded investigation of
causal relationships.
Practical implications
By illuminating associations between patients’ perceptions of discrimination in medical set-
tings and quality of care outcomes, health care systems can be incentivized and guided in the
development of systemic improvement measures. Such interventions, including surveillance,
training, and policies, can be further informed by data regarding the types of behaviors and
clinical scenarios most commonly implicated in perceived discriminatory experiences. Aware-
ness of the need for this type of work is increasing, as highlighted by the Physicians’ Charter
which states that physicians must “work actively to eliminate discrimination in health care”
[49]. Though previous studies of the effectiveness of culturally competent care education have
shown mixed results [50], there is some evidence that completion of such interventions can
mediate greater patient satisfaction and greater follow-up appointment attendance [51]. Simi-
larly, medical schools have shown some success in reducing medical student implicit bias
through health disparities and culture competence curricula [52]. Strategies to specifically
address physician implicit bias have been proposed [53], but there is minimal implementation
of this type of training in practice [54].
Directions for future research
Larger and national studies of perceived discrimination in medical settings are needed to
assess the prevalence and consequences of this issue in the broader U.S. health care system
[10]. Future studies, following patient perceptions, health behaviors, and outcomes over time,
would help clarify which health care outcomes are most vulnerable to this type of perceived
discrimination. Learning health care systems working to reduce provider-based discrimina-
tion through professional training (such as implicit bias training) should carefully evaluate
and report on the efficacy of such systemic implementations. Ideally, objective health out-
comes from EMR data should be assessed to better understand the impact of health care dis-
crimination perceptions on health, as well as potential improvements resulting from system
Perceived discrimination in medical settings and quality of care
PLOS ONE | https://doi.org/10.1371/journal.pone.0215976 April 25, 2019 11 / 15
interventions. Ultimately, however, we must recognize that the factors contributing to health
disparities are vast, and extend far beyond the direct interactions between patients and health
professionals [2]. Further research into the influence of institutional racism and other social
determinants of health is needed to guide broader policy-making that might work synergisti-
cally with improvements in interpersonal health care experiences, with the ultimate goal of
improving health equity [10, 55].
Conclusions
Levels of perceived discrimination in medical settings over a lifetime are high for Blacks, Mexi-
cans, and Puerto Ricans in this sample from ten Chicago communities and this type of per-
ceived discrimination was strongly related to perceptions of the patient experience. While
racism is widely acknowledged (and considered a determinant of existing health disparities)
for Black populations, perceived discrimination in the medical setting represents an emerging issue to be addressed for the growing Hispanic populations and those who serve them. Our
findings further reveal that perceived discriminatory events are not limited to one type of
health care setting or role. More work is needed to identify, address, and, hopefully, prevent,
this type of interaction within our health care systems in order to improve patient experiences
and ultimately outcomes.
Acknowledgments
We are grateful to the Chicago residents who contributed to the Sinai Community Health Sur-
vey 2.0. We also thank our colleagues at the Sinai Urban Health Institute for their valuable
feedback on earlier drafts.
Author Contributions
Conceptualization: Maureen R. Benjamins.
Formal analysis: Maureen R. Benjamins.
Methodology: Maureen R. Benjamins.
Project administration: Maureen R. Benjamins.
Writing – original draft: Maureen R. Benjamins, Megan Middleton.
Writing – review & editing: Maureen R. Benjamins.
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