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Race/ethnicity, and Americans’ perceptions and experiences of over- and under-use of care: a cross-sectional study

BMC Health Services Research201515:443

https://doi.org/10.1186/s12913-015-1106-7

Received: 4 May 2015

Accepted: 23 September 2015

Published: 1 October 2015

Abstract

Background

Despite widespread documentation of racial/ethnic disparities in care (predominantly under-use of needed care), differences in population-wide attitudes or experiences about under- or overuse (care where harms may outweigh potential benefits) of care are not well understood. We examined whether race/ethnicity is associated with perceptions or experiences of overuse or underuse.

Methods

We conducted secondary analysis of a cross-sectional national telephone survey of nationally representative sample of 1238 American adults; 57.9 % female, 75.4 % Non-Hispanic White, 11.8 % Non-Hispanic Black, 10.1 % Hispanic. The main outcome measures are general perceptions and personal experiences of overuse and underuse, including cost-related dimensions of each.

Results

Bivariate results indicated that respondents of minority race/ethnicity generally viewed both overuse and underuse as bigger problems than did Whites, and reported more personal experiences of each. After adjustment, Hispanics were less likely than Whites to report personal experiences of overuse (odds ratio [OR] [95 % CI], 0.44 [0.23 to 0.86]), while Blacks and Others were more likely to report cost-related overuse (ORs [95 % CIs], 4.16 [2.30 to 7.51]; 3.55 [1.52 to 8.28], respectively). Non-Hispanic Others more often reported doctors’ protection from overuse (OR [95 % CI], 3.69 [1.75 to 7.78]). General concerns with underuse were more frequent among Blacks and Hispanics (ORs [95 % CIs], 3.07 [1.72 to 5.54]; 2.12 [1.24 to 3.61] respectively), while Others reported significantly fewer concerns (OR [95 % CI], 0.43 [0.23 to 0.80]).

Conclusions

Over- and underuse of medical care are important problems for many Americans, and experiences vary by race/ethnicity. Clinician communication and educational campaigns about appropriateness of care may need tailoring for varying population groups.

Keywords

Patient preferences Disparities Survey research

Background

Racial/ethnic disparities in receipt of health care are widely documented [1, 2], but most research has focused on underuse – patients not receiving needed and appropriate care — without also examining overuse—receipt of unneeded or inappropriate care that does not improve health outcomes, whose harms and risks exceed its benefits [35]. The soaring U.S. health spending and suboptimal outcomes have put pressure on the US health care system to reduce costs and improve the quality of health care. Today, there are multiple efforts underway to increase awareness of the issue of overuse, as the elimination of unnecessary medical care may reduce waste and prevent potential harm. Most prior disparities studies have examined actual receipt of care among clinically similar patients, so little is known about attitudes or experiences about under- or over-use among the general American population. Such attitudes and perceptions are important to understand, as they might be a target for future interventions to improve the appropriateness of care.

Despite the increasing concerns regarding overuse of care, as exemplified by the American Board of Internal Medicine Foundation’s “Choosing Wisely” campaign, efforts by Consumer Reports, and others [4, 6, 7], and longstanding concerns about underuse [1], we could not locate any published reports of population-based studies of attitudes or related experiences with over- or underuse of health care, or how these vary by race. Thus, the goal of this study was to examine racial/ethnic differences in Americans’ attitudes and experiences about overuse and underuse of medical care. We hypothesized, given known disparities in underuse of care, that racial/ethnic minority respondents would be more likely to report both general concerns and personal experiences with underuse. We posited that given Whites’ greater relative socioeconomic advantage [8] (that might foster use of more care, including more inappropriate care [912]), Whites might perceive and experience more overuse.

Methods

Overview

Using publicly available data from a nationally representative sample of American adults, we examined the extent to which race/ethnicity was associated with perceptions and experiences of overuse and underuse. We developed our hypotheses prior to inspection of the data. Institutional Review Board approval was obtained from the Boston University Institutional Review Board with waiver of consent.

Data

We used cross-sectional national telephone survey data from “The Public and the Health Care Delivery System”, which examined numerous aspects of the public’s attitudes and experiences [13]. This effort was jointly sponsored by National Public Radio (NPR), the Kaiser Family Foundation (KFF) and the Harvard School of Public Health (HSPH). Survey fieldwork was done by telephone in March, 2009 by Social Science Research Solutions, of a nationally representative sample of 1238 randomly selected respondents ages 18 and over. Interviews were conducted in English and Spanish. In the data file, all groups were weighted to reflect their actual distribution in the nation.

We accessed the data in May, 2013 through the Roper Center for Public Opinion Research at the University of Connecticut’s iPOLL Databank, to conduct analyses to address different scientific questions than those originally examined or reported by the study’s sponsors. The Boston University Institutional Review Board determined that this study was exempt from human studies review.

Study variables

Independent variable

Race/ethnicity was classified as non-Hispanic White (hereafter “White”), non-Hispanic Black (“Black”), Hispanic, and non-Hispanic Others (“Others”), obtained via respondent self-report.

Outcomes

We examined two domains of respondents’ self-reported outcomes: perceptions about and experiences with 1) overuse of care, 2) underuse of care.

Overuse was assessed with 4 questions: 1) general overuse (“Too many patients getting medical tests and treatments that they don’t really need… is a major problem, minor problem, or not a problem”; responses to the latter two categories combined, don’t know responses deleted (3 %)). 2) personal experiences with overuse (“In the past 2 years, do you think you have received a medical test or treatment that was probably NOT necessary?”; response options were yes/no/don’t know (latter deleted; 1 %)). 3) cost-related overuse (“In the past 2 years, do you think your doctor has ever recommended an expensive medical test or treatment for you when a less expensive alternative would work just as well?”; response options: yes/no/don’t know (latter deleted; 5 %)). 4) experiences with physicians protecting them from overuse (“In the past 2 years, has a doctor denied you a medical test or treatment that you wanted because they thought it was not medically necessary?”; yes/no, don’t know (1 %; deleted)).

Underuse was assessed with 3 questions: 1) general underuse of care (“Too many patients NOT getting the medical tests and treatments that they need is a major problem, minor problem, or not a problem”, responses to the latter two categories combined, don’t know responses deleted (2 %)). 2) personal experiences with underuse (“In the past two years, has there been a time when you did NOT receive a medical test or treatment when you needed it?”; response options were yes/no/don’t know (latter deleted; 0.5 %)). 3) cost-related underuse (“In the past two years, do you think your doctor has ever recommended a medical test or treatment for you that is not as effective as other treatments but is less expensive?”; yes/no, don’t know (4 %; deleted)).

Covariates

We assessed sociodemographic factors which might affect individuals’ perceptions or experiences of care, or which might modify the association between race and the outcomes, including age (categorized as 18–29, 30–49, 50–64, 65 and over), gender, education (grouped into attended high school, graduated high school, attended college, and graduated college), family income (all-source income before taxes in 2008, dichotomized as <$50,000 and $50,000+), self-reported health status (categories: excellent, very good, good, fair or poor (latter two combined)), and presence/absence of insurance coverage (‘insured’ category including both private and government insurance (e.g., Medicare, Medicaid)).

Statistical analysis

We first conducted bivariate analyses to explore the associations of race and other sociodemographic factors with the outcomes. Significance of associations between dependent and independent variables was determined by Pearson chi-square statistics if responses were dichotomous or by Mantel-Haenszel chi-square statistics for ordinal responses. All selected covariates were significantly associated with one or more of the outcomes, so all were later included in multivariate analyses. We then performed multivariate logistic regression analyses to examine whether race was significantly associated with the outcomes, after adjusting for covariates. Questions with more than two response options were recoded as dichotomous, as indicated above. To address issues of nonresponse bias, sampling weights were developed using US Census data, to reflect respondents’ actual distribution in the nation, which were supplied with the dataset and used in the analyses. Statistical significance was estimated at the level of p <0.05. All analyses were performed using SAS, version 9.3.1.

Results

Demographic characteristics of the 1238 respondents showed that the majority of respondents were White (75 %), with about 12 % Black and 10 % Hispanic, and 58 % female (Table 1). More than 90 % of respondents were aged ≥30. About two-thirds of the participants attended or graduated college. Half of the subjects reported total family income from all sources before taxes less than $50,000. Almost half of the respondents reported excellent/very good health, and 90 % had some form of health insurance.
Table 1

Demographic characteristics of the sample (N = 1238)

Characteristics

% of subjects

Race/Ethnicity

 Non-Hispanic White

74.3 %

 Non-Hispanic Black

11.6 %

 Hispanic

9.9 %

 Non-Hispanic Others

2.7 %

 N/A

1.5 %

Gender

 Male

43.9 %

 Female

56.1 %

Age

 18–29

6.3 %

 30–49

32.0 %

 50–64

31.4 %

 65+

30.1 %

 N/A

0.2 %

Education

 Attended high school

11.1 %

 Graduated high school

24.9 %

 Attended college

22.3 %

 Graduated college

41.5 %

 N/A

0.2 %

Family incomea

 <$50,000

44.1 %

 $50,000+

44.4 %

 N/A

11.5 %

Self-reported health status

 Excellent

16.8 %

 Very good

32.5 %

 Good

27.8 %

 Fair/Good

22.5 %

 N/A

0.4 %

Insurance status

 Uninsured

9.9 %

 Insured

90.0 %

 N/A

0.1 %

aTotal family income from all sources before taxes in 2008

Overuse of care

Overall, 50 % of respondents felt that general overuse was a major problem, 14 % had personal experiences of overuse, 8 % reported experiences of cost-related overuse, and 8.5 % reported experiences of physicians protecting them from overuse. Bivariate results (Table 2) showed that race/ethnicity was consistently associated with perceptions of both general and personal overuse of health care, with racial/ethnic minorities generally reporting greater concerns with general overuse than Whites; Blacks and Others were more likely than Whites to report personal experiences with overuse, while Hispanics were least likely to report personal overuse. All racial/ethnic minority groups were more likely than Whites to report cost-related overuse, as well as doctors protecting them from overuse. Most other sociodemographic characteristics were significantly associated with perceptions of doctors protecting them from overuse, such that all racial/ethnic minorities, women, younger respondents, those who had attended but not graduated from high school or college, with lower incomes or poorer health status were more likely to report such experiences than Others, but there was no clear pattern as to which other sociodemographic factors were associated with the three other overuse items.
Table 2

Bivariate associations between sociodemographic characteristics and dependent variables

 

Overuse

Underuse

General overuse a problem

Personal experiences with overuse

Cost-related overuse

Experiences with physicians protecting against overuse

General underuse a problem

Personal experiences with underuse

Cost-related underuse

Major problem (%)

Minor/no problem (%)

Yes (%)

No (%)

Yes (%)

No (%)

Yes (%)

No (%)

Major problem (%)

Minor/no problem (%)

Yes (%)

No (%)

Yes (%)

No (%)

Overall distribution

50.0

50.0

13.9

86.1

8.0

92.0

8.5

91.5

66.4

33.6

11.1

88.9

8.5

91.5

Race/Ethnicity

 Non-Hispanic White

46.8

53.2

13.3

86.7

5.5

94.5

7.2

92.8

61.7

38.3

9.6

90.4

6.8

93.2

 Non-Hispanic Black

56.9

43.1

15.8

84.2

19.5

80.5

11.2

88.8

84.4

15.6

16.7

83.3

15.4

84.6

 Hispanic

62.3

37.7

10.6

89.4

9.9

90.1

11.4

88.6

80.3

19.7

11.4

88.6

11.5

88.5

 Non-Hispanic Others

54.8

45.2

33.3

66.7

23.3

76.7

27.3

72.7

60.6

39.4

21.2

78.8

15.2

84.8

p-value

0.029

0.001

<.001

<.001

<.001

0.026

0.002

Gender

 Male

50.7

49.3

14.0

86.0

8.0

92.0

6.5

93.5

59.9

40.1

8.0

92.0

8.1

91.9

 Female

49.0

51.0

13.8

86.2

8.0

92.0

10.0

90.0

71.6

28.4

13.5

86.5

8.8

91.2

p-value

0.295

0.979

0.679

0.021

<.001

<.001

0.731

Age

 18–29

53.8

46.2

25.3

74.7

10.4

89.6

14.1

85.9

77.9

22.1

24.4

75.6

7.8

92.2

 30–49

46.1

53.9

14.5

85.5

9.6

90.4

9.7

90.3

66.5

33.5

14.3

85.7

10.8

89.2

 50–64

50.1

49.9

14.0

86.0

7.8

92.2

9.9

90.1

69.6

30.4

12.1

87.9

10.0

90.0

 65+

52.4

47.6

11.0

89.0

5.8

94.2

4.3

95.7

60.7

39.3

3.8

96.2

4.4

95.6

p-value

0.815

<.001

0.485

0.003

0.009

<.001

0.100

Education

 Attended high school

65.1

34.9

14.2

85.8

12.3

87.7

10.4

89.6

70.2

29.8

15.4

84.6

9.2

90.8

 Graduated high school

54.7

45.3

12.2

87.8

9.7

90.3

7.2

92.8

71.5

28.5

12.4

87.6

9.2

90.8

 Attended college

47.6

52.4

15.8

84.2

7.7

92.3

11.6

88.4

69.5

30.5

13.1

86.9

10.6

89.4

 Graduated college

44.2

55.8

14.0

86.0

6.1

93.9

7.1

92.9

60.8

39.2

8.1

91.9

6.8

93.2

p-value

<.001

0.063

0.293

0.001

0.004

0.004

0.058

Family income

 <$50,000

54.8

45.2

13.6

86.4

10.0

90.0

9.8

90.2

73.5

26.5

13.5

86.5

10.5

89.5

 $50,000+

46.2

53.8

15.1

84.9

5.7

94.3

7.0

93.0

60.5

39.5

7.7

92.3

6.4

93.6

p-value

0.032

0.211

0.003

0.012

<.001

<.001

<.001

Self-reported health

 Excellent

53.2

46.8

13.6

86.4

6.4

93.6

3.9

96.1

54.7

45.3

5.8

94.2

3.5

96.5

 Very good

46.3

53.7

10.8

89.2

4.7

95.3

7.5

92.5

62.8

37.2

7.8

92.3

7.8

92.2

 Good

46.2

53.8

13.5

86.5

8.6

91.4

9.4

90.6

69.5

30.5

10.5

89.5

7.6

92.4

 Fair/Poor

56.7

43.3

19.1

80.9

13.5

86.5

12.3

87.7

76.5

23.5

20.3

79.7

14.6

85.4

p-value

0.521

0.007

0.085

0.003

<.001

<.001

<.001

Insurance status

 Uninsured

51.7

48.3

13.9

86.1

10.9

89.1

12.3

87.7

81.5

18.5

27.9

72.1

16.7

83.3

 Insured

49.4

50.6

13.9

86.1

7.7

92.3

8.0

92.0

64.7

35.3

9.2

90.8

7.5

92.5

p-value

0.148

0.380

0.894

0.144

<.001

<.001

<.001

After adjusting for covariates in multivariate regressions, race/ethnicity remained a significant predictor of 3 overuse items, but not perceptions of general overuse (Table 3). Hispanics were less than half as likely as Whites to report personal overuse (adjusted odds ratio [AOR] [95 % CI], 0.44 [0.23 to 0.86]). Blacks and Others were three to four times more likely to report cost-related overuse (AORs [95 % CIs], 4.16 [2.30 to 7.51] and 3.35 [1.52 to 8.28], respectively). Non-Hispanic Others were more than three times more likely to report physicians protecting them from overuse (AOR [95 % CI], 3.69 [1.75 to 7.78]).
Table 3

Multivariate analyses: overuse of carea

 

General overuse (Modelling ‘yes, major problem)

Personal experience with overuse (Modelling ‘yes’)

Cost-related overuse (Modelling ‘yes’)

Physician protection from overuse (Modelling ‘yes’)

N

959

974

948

973

Race/Ethnicity

 Non-Hispanic White (REF)

    

 Non-Hispanic Black

1.22 (0.79, 1.88)

1.48 (0.87, 2.50)

4.16 (2.30, 7.51)

1.68 (0.88, 3.20)

 Hispanic

1.39 (0.90, 2.16)

0.44 (0.23, 0.86)

1.88 (0.93, 3.79)

0.99 (0.50, 1.97)

 Non-Hispanic Other

1.13 (0.62, 2.05)

1.20 (0.59, 2.46)

3.55 (1.52, 8.28)

3.69 (1.75, 7.78)

Gender

 Male (REF)

    

 Female

0.87 (0.67, 1.14)

1.09 (0.75, 1.56)

0.99 (0.62, 1.60)

1.60 (1.01, 2.54)

Age

 18–29 (REF)

    

 30–49

0.66 (0.45, 0.95)

0.45 (0.29, 0.72)

1.03 (0.55, 1.93)

0.49 (0.28, 0.86)

 50–64

0.75 (0.49, 1.13)

0.31 (0.18, 0.54)

0.77 (0.36, 1.64)

0.41 (0.21, 0.79)

 65+

0.74 (0.46, 1.19)

0.27 (0.14, 0.52)

0.66 (0.28, 1.58)

0.19 (0.08, 0.48)

Education

 Attended high school (REF)

    

 Graduated high school

0.80 (0.50, 1.26)

0.85 (0.46, 1.58)

1.01 (0.48, 2.11)

0.53 (0.26, 1.09)

 Attended college

0.54 (0.33, 0.88)

1.49 (0.80, 2.79)

1.16 (0.52, 2.58)

1.05 (0.51, 2.15)

 Graduated college

0.44 (0.26, 0.73)

1.06 (0.54, 2.09)

1.09 (0.46, 2.62)

0.78 (0.35, 1.74)

Family incomeb

 <$50k (REF)

    

 $50,000+

0.96 (0.69, 1.33)

0.92 (0.60, 1.41)

0.56 (0.31, 1.00)

0.78 (0.46, 1.31)

Self-reported health status

 Fair/Poor (REF)

    

 Excellent

1.17 (0.74, 1.85)

0.43 (0.23, 0.81)

0.82 (0.38, 1.77)

0.25 (0.10, 0.63)

 Very good

0.89 (0.60, 1.31)

0.44 (0.26, 0.73)

0.53 (0.27, 1.07)

0.46 (0.24, 0.88)

 Good

0.85 (0.57, 1.26)

0.57 (0.35, 0.95)

0.82 (0.43, 1.54)

0.99 (0.56, 1.78)

Insurance status

 Uninsured (REF)

    

 Insured

1.72 (1.13, 2.62)

1.64 (0.92, 2.92)

1.48 (0.74, 2.95)

1.41 (0.74, 2.69)

aLogistic regressions models controlled for sample weights; all models included adjusted for all covariates

bTotal family income from all sources before taxes in 2008

Table 4

Multivariate analyses: underuse of carea

 

General underuse (Modelling ‘yes, major problem)

Personal experiences with underuse (Modelling ‘yes’)

Cost-related underuse (Modelling ‘yes’)

N

968

978

955

Race/Ethnicity

 Non-Hispanic White (REF)

   

 Non-Hispanic Black

3.07 (1.72, 5.45)

1.16 (0.63, 2.11)

1.72 (0.89, 3.29)

 Hispanic

2.12 (1.24, 3.61)

0.61 (0.33, 1.13)

0.97 (0.47, 2.02)

 Non-Hispanic other

0.43 (0.23, 0.80)

1.17 (0.52, 2.63)

0.49 (0.15, 1.59)

Gender

 Male (REF)

   

 Female

1.46 (1.09, 1.95)

1.99 (1.30, 3.05)

1.10 (0.68, 1.79)

Age

 18–29 (REF)

   

 30–49

0.72 (0.47, 1.09)

0.74 (0.45, 1.21)

1.98 (0.99, 3.98)

 50–64

0.78 (0.49, 1.24)

0.43 (0.24, 0.79)

1.56 (0.72, 3.38)

 65+

0.53 (0.31, 0.88)

0.09 (0.03, 0.26)

0.67 (0.23, 1.92)

Education

 Attended high school REF)

   

 Graduated high school

1.49 (0.90, 2.47)

0.37 (0.20, 0.70)

1.49 (0.67, 3.29)

 Attended college

1.87 (1.08, 3.22)

1.09 (0.58, 2.04)

3.16 (1.38, 7.21)

 Graduated college

1.56 (0.90, 2.71)

0.77 (0.38, 1.57)

2.32 (0.94, 5.74)

Family incomeb

 <$50k (REF)

   

 $50,000+

0.73 (0.51, 1.04)

0.50 (0.30, 0.82)

0.61 (0.34, 1.10)

Self-reported health status

 Fair/Poor (REF)

   

 Excellent

0.47 (0.29, 0.78)

0.16 (0.07, 0.35)

0.17 (0.06, 0.45)

 Very good

0.85 (0.55, 1.31)

0.30 (0.17, 0.52)

0.29 (0.15, 0.55)

 Good

0.93 (0.60, 1.44)

0.37 (0.21, 0.64)

0.37 (0.20, 0.70)

Insurance status

 Uninsured (REF)

   

 Insured

0.62 (0.38, 1.03)

0.87 (0.51, 1.47)

0.52 (0.28, 0.97)

Reference groups: NH-White, Male, Age: 18–29, Education: attended high school, Family Income: <$50k, Self-Report Health Status: Fair/Good

aLogistic regressions models controlled for sample weights; all models included adjusted for all covariates

bTotal family income from all sources before taxes in 2008

Underuse of care

Overall, 66 % of respondents felt that general underuse was a problem, 11 % had personally experienced underuse, and 8.5 % reported cost-related underuse. In bivariate analyses, minorities, less educationally or economically advantaged individuals and the uninsured had greater general concerns about underuse. Non-Hispanic Blacks were more likely than all Others to perceive general underuse as a problem, were more likely than Hispanics and Whites to report personal experiences of underuse, and to indicate that they had experienced cost-related underuse.

Race/ethnicity remained a significant predictor for just one dimension of underuse, in the multivariate regressions (Table 4). Blacks and Hispanics were more likely than Whites to report general concerns with underuse (AORs [95 % CIs], 3.07 [1.72 to 5.45], and 2.12 [1.24 to 3.61], respectively), but Others were less likely (AOR [95 % CI], 0.43 [0.23 to 0.80]). Race/ethnicity was not associated with personal experiences with underuse or cost-related underuse, after adjustment.

Discussion

We examined race/ethnicity differences in Americans’ attitudes about and experiences with overuse and underuse of medical care. Our hypothesis that racial/ethnic minority respondents would be more likely to report both general concerns and personal experiences with underuse, was supported in the bivariate results and by the multivariate results for the general question about underuse, but not with regard to personal or cost-related experiences of underuse. Though we expected that Whites would perceive and experience more overuse, multivariate results indicated no race differences in general perceptions of overuse, with only Hispanics reporting fewer personal experiences of overuse than Whites. Conversely, both Blacks and Others were more likely to report cost-related overuse, while Others more often reported their doctors protecting them from overuse.

This study was limited by the age of the data, which was collected in 2009 and could be considered old. However, in the absence of other national surveys of attitudes and experiences about overuse and underuse in this era of great interest in the topic, these data still have significant value, particularly since deeply held attitudes are often enduring and difficult to change [14]. The fact that these data precede the introduction of national campaigns such as Choosing Wisely gives these data value as a baseline indicator about American attitudes, prior to the recent increase in attention to the issue of overuse. The data are also limited by the fact that they were derived from self-report, without objective assessments of actual care received or its appropriateness, or of conversations with doctors; however, the reliability of patient self-reports about their clinical experiences has been validated [15], and support the value of these data. Finally, the representativeness of the sample should be considered. When compared to results from the 2010 US Census [16], this study undersampled Hispanics, males, and the uninsured [9], but oversampled Whites, the elderly, the insured and individuals with poorer health. While 22 % had attended college and 42 % of the sample graduated college, this is roughly similar to the 23 % attending college and 38 % graduating college, as reported in national statistics from the American Community survey [17]. Thus, it may be especially notable that race/ethnicity differences were found, given the lower proportions of some minority groups, better health, and greater rates of insurance in the study sample.

Blacks’ and Hispanics’ reports of more general, but not personal or cost-related concerns about underuse might reflect respondents’ awareness of the societal problem of underuse, but an inability to discern when they themselves are not receiving needed and appropriate care. If so, the need to tailor programs, policies and educational campaigns designed to heighten patients’ understandings of appropriate vs. inappropriate care becomes increasingly salient. Perhaps these findings reflect generally high degrees of trust in one’s own personal doctor, versus the medical system as a whole [18], or patients’ inability to critically evaluate their doctors’ recommendations [19, 20]. Educational campaigns, such as Choosing Wisely — begun in 2012 to raise Americans’ consciousness about issues of overuse [21] — aim to foster patients’ ability to more critically evaluate physician recommendations, and may help educate patients lack of awareness of personal over- and underuse. Similarly, insurers’ provision of health information, patient navigators and other programs to help patients navigate the health system might need to be tailored, or at least made sensitive, to the likelihood that patients from varying groups bring with them widely varying attitudes and experiences about the system.

Conclusions

These findings indicate that while many Americans feel that over- and underuse of medical care are important problems, some of these perceptions vary significantly by race and ethnicity, suggesting significant racial/ethnic gaps in perceptions and experiences with medical care among the American public. Some of these concerns could potentially be ameliorated in clinical settings through better communication or health information with patients, especially regarding the appropriateness of treatment recommendations. These variations in Americans’ perceptions are also important to recognize by those leading educational campaigns, such as the ABIM Foundation’s Choosing Wisely campaign, or patient education efforts by Consumer Reports, to educate Americans about the issues regarding overuse. The dynamics are also salient for disparities researchers and others addressing issues of underuse. Insofar as “one size does not fit all”, Americans’ attitudes about overuse and underuse of medical care varies with personal characteristics and group membership. Educational materials and informational campaigns may need tailored messages and messaging strategies for varying patient population groups, and efforts to enhance physicians’ skills in help patients choose wisely [22] need to ensure that physicians are equipped and skilled in providing patients of all backgrounds with the information they need to ultimately improve the equity and quality of care for all.

Abbreviations

NPR: 

National Public Radio

KFF: 

Kaiser Family Foundation

HSPH: 

Harvard School of Public Health

Declarations

Acknowledgements

The authors would like to thank the original team who developed and fielded the survey included Mollyann Brodie, Ph.D., Liz Hamel, Claudia Deane and Carolina Gutiérrez (KFF); Professor Robert Blendon, Sc.D., and John Benson, M.A. (HSPH); and Anne Gudenkauf, Joe Neel, Julie Rovner, Joanne Silberner, Richard Knox, Joseph Shapiro and April Fulton (NPR).

Funding

Dr. Kressin is supported in part by a Research Career Scientist award from the Department of Veterans Affairs, Health Services Research & Development Service (RCS 02-066-1).

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Section of General Internal Medicine, Boston University School of Medicine
(2)
VA Boston Healthcare System
(3)
Health Policy and Management Department, Boston University School of Public Health

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Copyright

© Kressin and Lin. 2015

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