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Journal of General Internal Medicine

, Volume 33, Issue 3, pp 305–331 | Cite as

Racial, Ethnic, and Gender Equity in Veteran Satisfaction with Health Care in the Veterans Affairs Health Care System

  • Susan L. Zickmund
  • Kelly H. Burkitt
  • Shasha Gao
  • Roslyn A. Stone
  • Audrey L. Jones
  • Leslie R. M. Hausmann
  • Galen E. Switzer
  • Sonya Borrero
  • Keri L. Rodriguez
  • Michael J. Fine
Original Research

Abstract

Background

Patient satisfaction is an important dimension of health care quality. The Veterans Health Administration (VA) is committed to providing high-quality care to an increasingly diverse patient population.

Objective

To assess Veteran satisfaction with VA health care by race/ethnicity and gender.

Design and Participants

We conducted semi-structured telephone interviews with gender-specific stratified samples of black, white, and Hispanic Veterans from 25 predominantly minority-serving VA Medical Centers from June 2013 to January 2015.

Main Measures

Satisfaction with health care was assessed in 16 domains using five-point Likert scales. We compared the proportions of Veterans who were very satisfied, somewhat satisfied, and less than satisfied (i.e., neither satisfied nor dissatisfied, somewhat dissatisfied, or very dissatisfied) in each domain, and used random-effects multinomial regression to estimate racial/ethnic differences by gender and gender differences by race/ethnicity.

Key Results

Interviews were completed for 1222 of the 1929 Veterans known to be eligible for the interview (63.3%), including 421 white, 389 black, and 396 Hispanic Veterans, 616 of whom were female. Veterans were less likely to be somewhat satisfied or less than satisfied versus very satisfied with care in each of the 16 domains. The highest satisfaction ratings were reported for costs, outpatient facilities, and pharmacy (74–76% very satisfied); the lowest ratings were reported for access, pain management, and mental health care (21–24% less than satisfied). None of the joint tests of racial/ethnic or gender differences in satisfaction (simultaneously comparing all three satisfaction levels) was statistically significant (p > 0.05). Pairwise comparisons of specific levels of satisfaction revealed racial/ethnic differences by gender in three domains and gender differences by race/ethnicity in five domains, with no consistent directionality across demographic subgroups.

Conclusions

Our multisite interviews of a diverse sample of Veterans at primarily minority-serving sites showed generally high levels of health care satisfaction across 16 domains, with few quantitative differences by race/ethnicity or gender.

KEY WORDS

patient satisfaction health care disparities veterans 

INTRODUCTION

Patient satisfaction is an important dimension of health care quality, with meaningful secondary benefits.1,2 Patients who are more satisfied with their care are more likely to demonstrate positive health behaviors, such as improved self-care, increased adherence to prescribed medications, and acceptance of provider recommendations.3,4 Measures of patient satisfaction are used to grade the effectiveness of medical providers and health care systems,5 and are increasingly linked to provider and hospital payments.6

As the largest integrated health care system in the United States (US), the Veterans Health Administration (VA) systematically tracks patient satisfaction through the national Survey of Health care Experiences of Patients (SHEP),7,8 and is committed to operating a “health care network that anticipates and meets the needs of enrolled Veterans, in general … and the most vulnerable Veterans, in particular.”9 While satisfaction ratings assess the extent to which patients are happy with care, measures of health care experiences assess how frequently positive interactions with care occur (e.g., how often providers listen carefully).10,11 Measures of health care experiences are less subjective measures of health care quality.11 Prior studies of racial/ethnic and gender differences in VA health care experiences have revealed some inequities among these vulnerable patient populations, with no consistent pattern of differences across studies.2,7,8,1214

In studies of racial/ethnic differences, black and Hispanic Veterans have reported more negative and fewer positive health care experiences than whites,7,12,13 with a majority of the observed differences attributed to between-facility variations in experiences with care.7,12 Gender differences in VA health care experience have been less consistently documented, with some studies reporting lower satisfaction among female Veterans, particularly for inpatient care,8 while others reported no gender differences in patient experience12 or reported more positive experiences among female Veterans in some domains of outpatient care.12

Previous studies of racial/ethnic and gender differences in health care satisfaction among Veterans were based on small samples,2 assessed experiences in a limited set of health care domains,1517 or were conducted prior to recent VA initiatives aimed at making the health care environment more welcoming to female Veterans.8,18 To better understand racial/ethnic and gender variations in health care satisfaction, we conducted a large mixed-methods evaluation of Veteran satisfaction with outpatient, inpatient, and specialist care in a diverse sample of Veterans from predominantly minority-serving VA Medical Centers (VAMCs). In this report, we compare satisfaction ratings by race/ethnicity and gender.

METHODS

Design

We identified potential participants from 25 VAMCs across the US, conducted a multi-step recruitment and consent process between June 2013 and January 2015, and interviewed eligible participants by telephone within 6 weeks of obtaining their written consent. Study procedures were approved by the local institutional review board.

Facility Selection

Preliminary analyses indicated that the majority of racial/ethnic minority Veterans (75%) received their VA health care at a relatively small number of VAMCs (25%). We used VA administrative data from fiscal year (FY) 2009 (October 2008 to September 2009) to identify 43 VAMCs that provided care to 70% of black and/or Hispanic Veterans in the US. From these facilities, we selected a diverse set of VAMCs, including 10 where the patient population was at least 30% black and/or Hispanic, 44 where 10% or fewer were black and/or Hispanic, and 11 that were chosen to ensure a diversity in size and geographic location. Characteristics of participating sites are summarized in Appendix 1.

Sampling

We used administrative records to identify Veterans with at least one outpatient visit at a participating VAMC in FY 2012 or 2013, excluding Veterans without valid contact information. From those eligible, we randomly selected 90 Veterans from each facility in each of six strata (i.e., non-Hispanic white, non-Hispanic black, Hispanic male, non-Hispanic white, non-Hispanic black, or Hispanic female), resulting in an initial sampling frame of 13,500 Veterans. In facilities with fewer than 90 Veterans per stratum, we randomly sampled Veterans of the same gender with unknown race or ethnicity.

Recruitment

Potentially eligible Veterans were mailed a brief study description with an option to opt out of screening by telephone or mail. We called Veterans who did not opt out to confirm study eligibility, excluding those who did not speak English or declined to self-report race, ethnicity, or gender. Once written informed consent was obtained, eligible participants were interviewed by a contracted professional survey research organization.

Recruitment was conducted in waves over time. In each wave, a stratified random sample of several hundred Veterans was drawn from the initial sampling frame. We discontinued recruitment within a facility-specific stratum when a target sample size of nine Veterans was achieved. We chose this target based on the feasibility of interviewing an adequate number of respondents within each stratum per site to achieve qualitative thematic saturation. Respondents received a $35 honorarium for participation.

Health Care Satisfaction

Our mixed-methods study obtained quantitative Likert-style satisfaction ratings and asked qualitative open-ended questions to ascertain patient experiences that influenced satisfaction ratings. Standard measures of patient experience typically focus on frequency of specific experiences when obtaining care and not on patient evaluations of whether these experiences were deemed satisfactory. The analysis below focuses on quantitative satisfaction ratings. Appendix 2 contains the full interview script.

We assessed satisfaction with care in 16 domains based on the VA’s validated SHEP7,8 and prior research,19 including overall, outpatient, and inpatient care; primary care, specialist, and mental health providers; provider communication and respect, coordination of care, physical facilities (main VAMCs, local outpatient clinics), cost of care, pharmacy, pain management, and women’s health. Lead-in questions ascertained domain applicability. For each applicable domain, patient satisfaction was assessed using a single item with a five-category Likert scale (i.e., very satisfied, somewhat satisfied, neither satisfied nor dissatisfied, somewhat dissatisfied, and very dissatisfied). We combined Likert responses in the three lowest categories due to sparse data, and classified this combined category as “less than satisfied.”

Race/Ethnicity, Gender, and Covariates

We classified race/ethnicity obtained from the interview as non-Hispanic white, non-Hispanic black, Hispanic, or other, and gender as male or female. The interview also assessed sociodemographic characteristics (Table 1). We assessed health literacy using a single item (i.e., “How confident are you filling out medical forms by yourself: extremely, quite a bit, somewhat, a little bit, not at all?”).20 We quantified comorbidity using self-reported conditions from the Charlson Comorbidity Index21 plus common mental health conditions among Veterans (i.e., depression, post-traumatic stress disorder [PTSD], and anxiety). We assessed health status using the single-item global health and 1-year prior health questions from the SF-36.22,23 We captured VA outpatient and inpatient health care utilization from VA administrative records in the 12 months prior to each participant’s interview date.
Table 1.

Respondent Demographic, Clinical, and Health Care Utilization Characteristics by Race/Ethnicity and Gender

Characteristics

White (N = 421)

Black (N = 389)

Hispanic (N = 396)

Male (N = 208)

Female (N = 213)

Male (N = 187)

Female (N = 202)

Male (N = 195)

Female (N = 201)

Age in years (mean, SD)*

65.7

6.76

55.1

6.39

59.7

5.63

50.1

6.06

57.0

7.29

44.9

6.27

Marital status (n, %)*

 Married/living as married

67

32.2

123

57.7

105

56.1

151

74.8

79

40.5

117

58.2

 Single/widowed/divorced/separated

141

67.8

89

41.8

82

43.9

51

25.2

116

59.5

83

41.3

Education level (n, %)*

  ≤ High school/GED

43

20.7

15

7.0

46

24.6

11

5.4

47

24.1

20

10.0

 Trade school/some college

79

38.0

96

45.1

94

50.3

94

46.5

93

47.7

87

43.3

  ≥ College graduate

83

39.9

97

45.5

47

25.1

94

46.5

55

28.2

93

46.3

Employment status (n, %)*

 Full-time

37

17.8

56

26.3

29

15.5

79

39.1

53

27.2

83

41.3

 Part-time

24

11.5

27

12.7

16

8.6

15

7.4

14

7.2

25

12.4

 Unemployed/homemaker/student

12

5.8

30

14.1

21

11.2

36

17.8

24

12.3

45

22.4

 Retired

118

56.7

60

28.2

76

40.6

33

16.3

73

37.4

27

13.4

 Disabled

16

7.7

39

18.3

44

23.5

38

18.8

31

15.9

21

10.4

Place of residence (n, %)*

 Own home

149

71.6

138

64.8

85

45.5

86

42.6

119

61.0

94

46.8

 Rented home/apartment

42

20.2

52

24.4

77

41.2

100

49.5

59

30.3

91

45.3

 Shared or no permanent housing

17

8.2

21

9.9

24

12.8

15

7.4

16

8.2

15

7.5

Children in household (n, %)*

25

12.0

52

24.4

32

17.1

69

34.2

60

30.8

77

38.3

Income (n, %)

  ≤ $19,999

44

21.2

52

24.4

70

37.4

44

21.8

45

23.1

45

22.4

  ≥ $20,000 to $49,999

87

41.8

93

43.7

64

34.2

84

41.6

90

46.2

75

37.3

  ≥ $50,000

69

33.2

62

29.1

49

26.2

68

33.7

54

27.7

72

35.8

Rural/highly rural (n, %)*

100

48.1

95

44.6

52

27.8

56

27.7

71

36.4

74

36.8

Military service era (n, %)

 Pre-Vietnam*

63

30.3

15

7.0

16

8.6

7

3.5

16

8.2

3

1.5

 Vietnam War*

119

57.2

67

31.5

103

55.1

29

14.4

97

49.7

22

10.9

 Post-Vietnam*

54

26.0

116

54.5

98

52.4

124

61.4

74

37.9

84

41.8

 Persian Gulf*

39

18.8

96

45.1

52

27.8

130

64.4

72

36.9

150

74.6

Health status (n, %)*

 Poor

22

10.6

16

7.5

21

11.2

16

7.9

20

10.3

18

9.0

 Fair

33

15.9

38

17.8

54

28.9

59

29.2

58

29.7

43

21.4

 Good

79

38.0

73

34.3

73

39.0

87

43.1

64

32.8

72

35.8

 Very good

50

24.0

70

32.9

34

18.2

30

14.9

40

20.5

54

26.9

 Excellent

24

11.5

15

7.0

4

2.1

10

5.0

13

6.7

14

7.0

Health compared to 1 year ago (n, %)

 Much worse

11

5.3

12

5.6

8

4.3

10

5.0

7

3.6

11

5.5

 Somewhat worse

55

26.4

33

15.5

30

16.0

31

15.3

47

24.1

44

21.9

 About the same

99

47.6

94

44.1

92

49.2

99

49.0

75

38.5

88

43.8

 Somewhat better

18

8.7

45

21.1

29

15.5

30

14.9

28

14.4

26

12.9

 Much better

25

12.0

28

13.1

28

15.0

32

15.8

37

19.0

32

15.9

Confidence with medical forms (n, %)*

 Not at all/A little bit/Somewhat

20

9.8

10

4.7

12

6.6

10

5.0

22

11.6

11

5.5

 Quite a bit

31

15.2

14

6.6

34

18.6

15

7.5

38

20.0

14

7.0

 Extremely

153

75.0

187

88.6

137

74.9

176

87.6

130

68.4

176

87.6

Comorbid conditions (n, %)

 Asthma

33

15.9

49

23.0

36

19.3

47

23.3

36

18.5

42

20.9

 Arthritis

114

54.8

125

58.7

107

57.2

115

56.9

97

49.7

85

42.3

 Cancer*

29

13.9

14

6.6

11

5.9

5

2.5

15

7.7

4

2.0

 Diabetes*

53

25.5

26

12.2

63

33.7

43

21.3

61

31.3

30

14.9

 Digestive or GI problems

36

17.3

54

25.4

30

16.0

59

29.2

33

16.9

47

23.4

 Heart disease*

53

25.5

21

9.9

30

16.0

22

10.9

39

20.0

14

7.0

 HIV or AIDS

4

1.9

0

0.0

5

2.7

3

1.5

5

2.6

0

0.0

 Kidney disease

12

5.8

5

2.3

16

8.6

7

3.5

11

5.6

1

0.5

 Liver problem

17

8.2

6

2.8

20

10.7

10

5.0

17

8.7

9

4.5

 Stroke or mini-stroke

20

9.6

15

7.0

10

5.3

9

4.5

16

8.2

6

3.0

 Depression*

64

30.8

94

44.1

77

41.2

99

49.0

88

45.1

103

51.2

 PTSD or anxiety disorder*

57

27.4

99

46.5

79

42.2

107

53.0

94

48.2

105

52.2

Number of comorbid conditions (n, %)

 0

32

15.4

22

10.3

26

13.9

32

15.8

23

11.8

40

19.9

 1

43

20.7

49

23.0

28

15.0

31

15.3

45

23.1

41

20.4

 2

45

21.6

51

23.9

50

26.7

39

19.3

32

16.4

38

18.9

 3

42

20.2

40

18.8

28

15.0

34

16.8

36

18.5

33

16.4

 4+

46

22.1

50

23.5

55

29.4

66

32.7

59

30.3

49

24.4

VA health care system utilization (n, %)

 Received all health care at VA

109

52.4

121

56.8

136

72.7

125

61.9

136

69.7

129

64.2

 Pain management in last 24 months*

90

43.3

127

59.6

112

59.9

152

75.2

102

52.3

125

62.2

 Used VA pharmacy in last 24 months

180

86.5

196

92.0

178

95.2

194

96.0

183

93.8

189

94.0

  ≥ 1 outpatient visit in last 12 months

200

96.2

203

95.3

182

97.3

195

96.5

184

94.4

191

95.0

  ≥ 1 PCP visit in past 12 months

190

91.3

188

88.3

175

93.6

188

93.1

175

89.7

182

90.5

  ≥ 1 MH visit in past 12 months*

56

26.9

85

39.9

83

44.4

98

48.5

79

40.5

92

45.8

 Hospitalized in past 12 months

20

9.6

26

12.2

38

20.3

25

12.4

20

10.3

15

7.5

VA health care system utilization (mean, SD)

 Number of outpatient visits* (mean SD)

14.7

8.67

18.4

10.71

22.5

13.93

24.8

13.31

21.2

14.55

17.4

9.17

 Number of primary care visits (mean SD)

4.7

3.89

5.5

2.75

5.3

2.88

6.5

3.87

5.2

2.74

5.2

2.29

 Number of mental health visits (mean SD)

7.3

6.18

12.9

9.37

3.4

10.11

14.4

8.57

15.5

15.26

10.9

6.31

 Hospital length of stay (mean SD)

20.0

29.70

14.1

10.38

13.5

7.95

6.9

4.75

26.9

19.72

7.9

7.27

Percentages are computed based on the column-specific denominators, and may not sum to 1 due to a small amount of missing data. Less than 1.5% of data are missing for marital status, education, employment status, place of residence, health status, health compared to 1 year ago, health literacy, and total number of self-reported comorbid conditions. For income, 3.2% of the observations are missing

Abbreviations: GED general equivalency diploma, GI gastrointestinal, MH mental health, PCP primary care provider, PTSD post-traumatic stress disorder, VA Department of Veterans Affairs

*p < 0.001; p < 0.01; p < 0.05

Statistical Analyses

We summarized baseline respondent characteristics by race/ethnicity and gender. We used chi-square statistics to compare categorical variables and analysis of variance to compare continuous variables, as shown in Table 1. We fit random-effects multinomial regression models using the GLIMMIX procedure in SAS software (version 9.3; SAS Institute Inc., Cary, NC, USA) to compare the facility-specific proportions of participants who were “less than” or “somewhat” versus “very” satisfied (reference level) for each domain, specifying a random effect to account for clustering of Veterans within VAMCs.

Because preliminary analyses indicated a significant interaction between race/ethnicity and gender, we modeled gender-specific associations between race/ethnicity and satisfaction for each domain. Each model included fixed effects for gender, age (centered to the overall mean age [55] and scaled by 10 years), race/ethnicity, and the gender-by-race/ethnicity interaction, and a random effect for site. We adjusted for age in all models to account for differences in the age distributions by race/ethnicity. We assessed gender-specific differences between race/ethnicity subgroups using two-parameter 0.05-level Wald tests that simultaneously compared “less than satisfied” and “somewhat satisfied” to “very satisfied”; we also report pairwise Wald tests comparing these response categories. We constructed gender-specific linear contrasts of satisfaction for black versus white and Hispanic versus white Veterans, and race/ethnicity-specific contrasts from the same statistical model to assess gender differences within each race/ethnicity category for all domains except women’s health. P-values of < 0.05 were considered statistically significant, with no adjustment made for multiple comparisons.

In a sensitivity analysis, we assessed potential confounding in the age-adjusted models by considering each of the covariates shown in Table 1. We included variables significant at the 0.10 level in the domain of outpatient care in all domain-specific multivariable models. For each domain-specific model, we then used a backwards selection approach (removing variables with p > 0.10) to identify a parsimonious set of covariates. We assessed whether conclusions from the age-adjusted models changed based on this statistical adjustment for potential confounders.

RESULTS

Recruitment

Among the 7565 Veterans who were mailed invitations, 3090 (40.8%) could not be contacted and 2063 (27.3%) declined to be screened for eligibility (Appendix 3). Interviews were completed for 1222 of the 1929 Veterans known to be eligible for the study (63.3%). Among those eligible, 531 (27.5%) did not provide consent for voice recording, and 159 interviews (8.2%) could not be completed before the end of the study. After excluding 16 Veterans with “other” self-reported race/ethnicity, our analytical sample included 1206 Veterans (421 white, 389 black, and 396 Hispanic), 616 of whom were women.

Respondent Characteristics

Black and Hispanic respondents were younger and served in more recent military service eras than did white respondents; they were also more likely to receive all of their medical care at the VA (Table 1). Compared to men of the same race/ethnicity, women were younger and more likely to be married, college-educated, employed full-time, living in households with children, and health-literate. Although some individual comorbid conditions were more prevalent in men than women (e.g., cancer, diabetes) and vice versa (e.g., depression, PTSD), the total number of conditions did not differ by race/ethnicity or gender.

Satisfaction with VA Health Care

Among 1196 respondents to the overall satisfaction question, 565 (47.2%) were very satisfied, 431 (36.0%) somewhat satisfied, and 200 (16.7%) less than satisfied with VA health care. Within each facility, a majority of respondents reported being somewhat or very satisfied with VA health care overall (Fig. 1).
Figure 1

Percentage of Veteran respondents less than satisfied, somewhat satisfied, and very satisfied with overall VA health care, by study facility. Facilities are numbered according to their documented percentage of white Veterans in the initial sampling frame, with 1 denoting the lowest percentage of whites (23.3%), and 22–25 denoting the participating facilities with the highest percentages of whites (62.7–85.6%, respectively).

Satisfaction with care varied across specific domains (Fig. 2). Most respondents (73.8–76.4%) reported being very satisfied with cost of care, physical community-based outpatient facilities, and pharmacy services. Some respondents (20.8–23.9%) reported being less than satisfied with mental health care, pain management, and access. For each domain, respondents were significantly less likely to report being somewhat or less than satisfied versus very satisfied with their VA care (p < 0.01 for each; Fig. 3 and Appendix 4).
Figure 2

Percentage of Veteran respondents less than satisfied, somewhat satisfied, and very satisfied with VA health care, by domain. Satisfaction with cost of care; physical aspects of the facility; the pharmacy; inpatient, specialist, and mental health care; pain management; and women’s health were only assessed when applicable. N indicates the number of valid survey responses to the satisfaction questions for each domain. Abbreviations: VAMC = Veterans Affairs Medical Center, CBOC = Community-Based Outpatient Clinic.

Figure 3

Domain-specific multinomial model comparisons of health care satisfaction for all Veteran respondents. Each set of two rate ratios (RRs) compares the probability of reporting being “less than satisfied” versus “very satisfied” (left entry) and the probability of reporting being “somewhat satisfied” versus “very satisfied” (right entry). RRs to the left of 1.0 favor “very satisfied”. Abbreviations: VAMC = Veterans Affairs Medical Center, CBOC = Community-Based Outpatient Clinic.

Differences in Satisfaction by Race/Ethnicity and Gender

No two-parameter Wald test of racial/ethnic or gender differences achieved statistical significance for overall satisfaction or other domains (Appendices 5, 6). However, pairwise comparisons showed some evidence of racial/ethnic differences in specific levels of satisfaction within three domains. In age-adjusted multinomial models, black men were less likely than white men to be less than (vs. very) satisfied with access (relative rate ratio [RRR] = 0.52, 95% CI = 0.28–0.97; Fig. 4 and Appendix 4). Hispanic men were more likely than white men to be somewhat (vs. very) satisfied with cost of care (RRR = 2.75, 95% CI = 1.13–6.72), and Hispanic women were less likely than white women to be somewhat (vs. very) satisfied with pharmacy services (RRR = 0.49, 95% CI = 0.25–0.97). Some CIs are wide because few Veterans reported being less than satisfied and some domains pertained to relatively few respondents.
Figure 4

Gender-specific comparisons of health care satisfaction by race/ethnicity. The set of relative rate ratios (RRRs) for each domain compares the gender-specific RRs of reporting “less than satisfied” versus “very satisfied” (left entry) and the RRs of reporting being “somewhat satisfied” versus “very satisfied” (right entry). RRRs to the left of 1.0 favor black (or Hispanic) Veterans being “very satisfied” relative to white Veterans of the same gender. Abbreviations: VAMC = Veterans Affairs Medical Center, CBOC = Community-Based Outpatient Clinic.

We identified some evidence of gender differences in levels of satisfaction by race/ethnicity in five domains. Black women were more likely than black men to be less than (vs. very) satisfied with pharmacy services (RRR = 2.98, 95% CI = 1.10–8.07; Fig. 5 and Appendix 6). White women were more likely than white men to be somewhat (vs. very) satisfied with outpatient care (RRR = 2.00, 95% CI = 1.08–3.70), cost of care (RRR = 2.46, 95% CI = 1.13–5.38), and respect (RRR = 2.52, 95% CI = 1.04–6.09). In contrast, black women were less likely than black men to be somewhat (vs. very) satisfied with specialist care (RRR = 0.49, 95% CI = 0.27–0.89).
Figure 5

Race/ethnicity-specific comparisons of health care satisfaction by gender. The set of relative rate ratios (RRRs) for each domain compares the race/ethnicity-specific RRs of reporting “less than satisfied” versus “very satisfied” (left entry) and the RRs of reporting being “somewhat satisfied” versus “very satisfied” (right entry). RRRs to the left of 1.0 favor female Veterans being “very satisfied” relative to male Veterans of the same race/ethnicity. Abbreviations: VAMC = Veterans Affairs Medical Center, CBOC = Community-Based Outpatient Clinic.

These age-adjusted results were essentially unchanged in domain-specific models adjusting for additional demographic, clinical, and health care utilization characteristics, though some p-values changed slightly (Appendices 7, 8).

A post hoc power calculation based on the observed sample sizes, intraclass correlation, and outcome distributions indicated that this study had 80% power to detect a gender-specific racial/ethnic difference of 17% in overall satisfaction (somewhat satisfied vs. very satisfied). A somewhat larger difference (25%) could be detected for the less than satisfied vs. very satisfied comparisons.

DISCUSSION

Our interviews with Veterans from predominantly minority-serving VA Medical Centers across the US demonstrated that for all 16 domains assessed, respondents were more likely to be very satisfied with health care than somewhat or less than satisfied. Despite generally high levels of reported satisfaction overall, we identified some variation in satisfaction by domain. We found only a few pairwise differences in specific levels of satisfaction (i.e., less than or somewhat satisfied versus very satisfied) by race/ethnicity or gender, with no consistent direction of effect within demographic subgroups. Although several domains could be targeted for improvement efforts, our findings suggest that the VA is meeting generally its goal to ensure positive and equitable health care satisfaction among a growing population of minority Veterans.

Our finding that 83% of respondents were somewhat or very satisfied with VA health care overall is consistent with a recent Gallup survey, which found that 78% of patients receiving care through the VA or military insurance were satisfied with care.24 Ratings of satisfaction in the Gallup survey were higher for participants receiving VA or military health care than for participants receiving care through Medicaid (77%), Medicare (75%), employer-sponsored insurance (69%), or individually purchased insurance (65%). In the current study, more than 70% of respondents reported being very satisfied with care in 7 of the 16 domains assessed, with the highest satisfaction reported for the cost of care, physical aspects of facilities, and pharmacy. Our finding of relatively high satisfaction with costs and pharmacy might be explained by VA efforts to minimize cost sharing for Veterans. For example, enrollees pay no monthly premiums or enrollment fees, and copayments and prescription costs in the VA are reduced compared to those in other health care systems.25

Our examination of satisfaction across a comprehensive set of domains identified areas of lower satisfaction that could help inform VA efforts to improve health care delivery. More than 20% of respondents were less than satisfied with general pain management, mental health care, and access. Dissatisfaction with pain management and mental health care is of concern, because these disorders are highly prevalent in the VA,26,27 and satisfaction has been linked to improved clinical outcomes.28 Our finding of relatively low satisfaction with access is consistent with concerns prompting passage of the Veterans Access, Choice, and Accountability Act of 2014,29,30 which coincided with our study. As more Veterans receive care in the community following passage of the Veterans Choice Act, longitudinal evaluations of Veteran satisfaction with access to VA and non-VA providers will be important in determining the policy’s success.

This study provides new insights into patient perceptions of care in VA facilities with relatively large concentrations of black and/or Hispanic patients. Contrary to prior studies,13 we identified little evidence of racial/ethnic disparities in health care satisfaction, with three exceptions. Our study provides some evidence that Hispanic men are less satisfied than white men with the cost of care, black men are more satisfied than white men with access to care, and Hispanic women are more satisfied than white women with pharmacy services. Previous national studies of racial/ethnic differences in experiences with VA health care found that a majority of black–white and Hispanic–white differences in health care experiences could be attributed to variations between facilities where blacks, whites, and Hispanics received care.7,12 Our finding of few racial/ethnic differences within VA facilities serving black and Hispanic patients supports previous results suggesting that efforts to improve health care satisfaction across racial/ethnic groups might begin by focusing on areas of dissatisfaction (e.g., access, mental health care) in those facilities where large numbers of black and Hispanic Veterans receive care.7

Our study also examined potential interactions between race/ethnicity and gender in predicting patient satisfaction. In contrast to previous studies, which found no gender differences12 or found more positive experiences among female than male Veterans,12 the current study provides some evidence that white women (vs. men) experience less satisfaction with outpatient care, costs, and respect, and that black women (vs. men) are less satisfied with pharmacy services but more satisfied with specialist care. While the VA appears to be making the health care environment welcoming to both male and female Veterans, varying patterns of gender differences across racial/ethnic groups suggest that efforts to further ensure gender equity may need to be culturally targeted.

Our study has some limitations. First, it focused on within-facility racial/ethnic and gender differences at primarily minority-serving facilities; results do not generalize to other VA facilities, and thus it is not possible to quantify the magnitude of between-facility differences in satisfaction by race/ethnicity or gender on a national level. Second, our study respondents represent a stratified sample of eligible Veterans, and the demographic composition of the sample does not reflect that of the populations at participating sites. Furthermore, we observed a modest response rate and were unable to assess potential bias due to inability to contact for screening, decline of screening, or refusal of consent for the voice recording. Unwillingness to participate could be associated with satisfaction. Third, the study was powered to detect pairwise differences in overall satisfaction by race/ethnicity within gender, but has limited power to detect differences in domains that are applicable to smaller subsets of Veterans, such as inpatient care. These statistical analyses are considered descriptive rather than inferential, and provide the background for the ongoing qualitative analysis. Finally, given the large number of statistical comparisons performed, some positive associations would be expected simply by chance.

In summary, this large, multisite study demonstrated generally high levels of satisfaction with VA health care across several outpatient, inpatient, and specialist domains in primarily minority-serving VA medical centers. We also identified some domains where satisfaction could be improved for all Veterans managed in minority-serving facilities, and more specifically for Hispanic men, black women, and white women. Understanding differences in satisfaction across health care domains and how these differences vary by race/ethnicity and gender will enable the VA to improve health care experiences for the increasingly diverse population of US Veterans.

Notes

Acknowledgments

This work was supported by Department of Veterans Affairs Health Services Research and Development Merit Review (IIR 100144) and Service Directed Research (13-425) awards. The content of this article is solely the responsibility of the authors and does not necessarily represent the views of the Department of Veterans Affairs or the United States Government.

Compliance with Ethical Standards

Conflict of Interest

All authors declare that they have no conflict of interest.

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Copyright information

© Society of General Internal Medicine (outside the USA) 2018

Authors and Affiliations

  • Susan L. Zickmund
    • 1
    • 2
  • Kelly H. Burkitt
    • 3
  • Shasha Gao
    • 3
  • Roslyn A. Stone
    • 3
    • 4
  • Audrey L. Jones
    • 1
    • 2
  • Leslie R. M. Hausmann
    • 3
    • 5
  • Galen E. Switzer
    • 3
    • 5
    • 6
  • Sonya Borrero
    • 3
    • 5
  • Keri L. Rodriguez
    • 3
    • 5
  • Michael J. Fine
    • 3
    • 5
  1. 1.Informatics, Decision-Enhancement and Analytic Sciences Center (IDEAS 2.0)VA Salt Lake City Health Care SystemSalt Lake CityUSA
  2. 2.Division of Epidemiology, Department of Internal MedicineUniversity of Utah School of MedicineSalt Lake CityUSA
  3. 3.Center for Health Equity Research and PromotionVA Pittsburgh Healthcare SystemPittsburghUSA
  4. 4.Department of BiostatisticsUniversity of Pittsburgh Graduate School of Public HealthPittsburghUSA
  5. 5.Division of General Internal Medicine, Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghUSA
  6. 6.Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghUSA

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