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Patient–physician racial and ethnic concordance and perceived medical errors
ARTICLE IN PRESS
Social Science & Medicine 63 (2006) 3060–3066 www.elsevier.com/locate/socscimed
Patient–physician racial and ethnic concordance and perceived medical errors Irena Stepanikova University of South Carolina, Columbia, SC, USA Available online 22 September 2006
Abstract In this paper, I use nationally representative survey data to examine the relationship between patient–physician racial/ ethnic concordance and perceived medical errors in the USA. After adjusting for potential confounding factors, we find that White patients treated by White physicians have 33% lower odds of reporting medical errors than White patients treated by non-White physicians. In contrast, patient–physician racial/ethnic concordance has no effect on perceived medical errors among non-White patients. The results suggest that the role of racial/ethnic concordance in perceptions of health care safety varies by patients’ racial/ethnic background. r 2006 Elsevier Ltd. All rights reserved. Keywords: Perceived medical errors; Race/ethnicity; USA; Patients
Main text Medical errors represent a serious threat to patient safety. Deaths resulting from medical errors in the United States range from 44,000 to 98,000 annually, exceeding those resulting from AIDS or motor vehicle accidents (Institute of Medicine, 1999). A more recent estimate of 225,000 deaths from errors and adverse effects makes iatrogenic events the third leading cause of death, exceeded only by heart disease and cancer (Starfield, 2000). The incidences of adverse events range between 3% and 17% of all hospitalizations (von Laue, Schwappach, & Koeck, 2003). In outpatient care, errors occur in 4–18% of visits (Weingart, Wilson, Gibberd, & Harrison, 2000). The estimated national costs of preventable adverse events range between Tel.: +1 803 777 6866.
E-mail address: [email protected]. 0277-9536/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.socscimed.2006.08.015
17 and 29 billion annually (Institute of Medicine, 1999). Many Americans are concerned about medical errors. Thirty-three percent (National Patient Safety Foundation, 1997) to 42% (Blendon, DesRoches, & Brodie, 2002) of respondents to national surveys report having experienced medical errors either personally or in their families. Respondents often associate these errors with serious consequences, including severe pain, loss of time at work or school, disability, and death (The Kaiser Family Foundation, 2004). Forty-seven percent of American adults disagree that the current health care system has adequate measures in place to prevent medical mistakes (National Patient Safety Foundation, 1997). The purpose of this study is to explore whether patient–physician racial/ethnic concordance, i.e., the match between the physician’s and the patient’s racial/ethnic backgrounds, is related to patients’
ARTICLE IN PRESS I. Stepanikova / Social Science & Medicine 63 (2006) 3060–3066
perceptions of medical errors. Research on patient safety has neglected this issue but we know that the lack of patient–physician racial/ethnic concordance is associated with worse health care outcomes, including lower patient satisfaction (LaVeist & Nuru-Jeter, 2002; Saha, Komaromy, Koepsell, & Bindman, 1999) and less participation in medical decision-making (Cooper-Patrick, Gallo, & Gonzales, 1999). Some minority patients believe that the lack of racial/ethnic concordance leads to worse physician–patient communication and decreases physicians’ empathy (Garcia, Paterniti, Romano, & Kravitz, 2003). How might patient–physician racial/ethnic concordance relate to patients’ perceptions of medical errors? I propose two parallel mechanisms. First, racial/ethnic concordance may decrease the likelihood that medical errors occur and hereby decrease patients’ perceptions of errors. Crosscultural and language barriers in racially/ethnically discordant relationships may make it difficult for physicians to obtain complete and accurate information from patients and may eventually lead to more frequent errors in the diagnosis and treatment. Second, patient–physician racial/ethnic concordance may reduce patients’ perceptions of medical errors, whether or not the errors actually occurred. Racial/ethnic concordance contributes to well-functioning, trustful patient–physician relationships. Patients treated by physicians of the same racial/ ethnic background, who enjoy trustful relationships, may be less likely to causally attribute adverse events or other types of negative experiences with the health care process and outcomes to their physicians’ negligence or error. These arguments lead me to hypothesize that patients in racially/ ethnically concordant patient– physician relationships are less likely to report medical errors than other patients. Data 2001 Survey on Disparities in Quality of Health Care, sponsored by The Commonwealth Fund, is a random-digit-dial telephone survey with 6722 adults (age 18 and older) residing in the continental United States. Telephone numbers from areas with a higher than average density of minority residents were over-sampled. Respondents reported their sources of, access to, and utilization of health care; experiences with health care; and socio-demographic characteristics. Since only respondents
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who reported having a regular physician and who saw a physician in the last year were asked about the physician’s race/ethnicity and about physician–patient communication, the analyses necessarily exclude respondents with no regular physician and those who have not recently received any health care. The final non-missing N after these exclusions is 4385. Data are missing randomly on the dependent variable.
Measures Respondents were asked, ‘‘Have you or any family member ever gotten sick or gotten worse as a result of going to the doctor’s office or being hospitalized?’’ Those who answered in the affirmative were asked, ‘‘Do you think this was due to a mistake made at the doctor’s office or hospital?’’ Perceived medical errors were coded as 1 for respondents who answered yes to both these questions and 0 for all others. Respondents’ reported their ethnicity (Hispanic or non-Hispanic) and race (White, Black, Asian, Native American, and Pacific Islander). Due to the small number of respondents, I collapse the last three racial categories into a single category, ‘‘other’’. To approximate English proficiency, I further distinguish between Hispanics who chose a Spanish interview and Hispanics who chose an English interview. Resulting categories for race/ethnicity/language are non-Hispanic Black, non-Hispanic White, Hispanic interviewed in Spanish, Hispanic interviewed in English, and other. Respondents also reported their regular physician’s race/ethnicity.1 Patient– physician racial/ethnic concordance was coded as 1 if the patient’s and physician’s race/ethnicity matched and 0 otherwise. Two aspects of physician–patient communication were measured. ‘‘The last time you visited a doctor, did the doctor listen to everything you had to say, to most, to some, or only a little of what you had to say?’’ (4 ¼ everything, 3 ¼ most, 2 ¼ some, 1 ¼ only a little) represented physicians’ listening skills. ‘‘Did you have questions about your care or treatment that you wanted to discuss but did not?’’ 1
To determine whether respondents have a regular source of care, they were asked: ‘‘Do you have a regular doctor or other health professional, such as a nurse or a midwife, you usually go to when you are sick or need health care?’’.
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(1 ¼ yes, 0 ¼ no) represented patients’ unanswered questions. For the place where care is usually delivered, respondents were asked, ‘‘Where do you usually go when you are sick or need health care?’’ ‘‘Doctor’s office or private clinic’’ was coded as 1. All other responses, including ‘‘community health center or other public clinic’’, ‘‘hospital outpatient department’’, ‘‘hospital emergency room’’, or ‘‘some other place’’, were coded as 0. For the insurance status, uninsured respondents are distinguished from respondents with health insurance (‘‘health insurance through your or someone else’s employer or work or health insurance bought directly by you or your family’’, ‘‘Medicaid’’; ‘‘Medicare’’; or ‘‘other government or state medical program such a CHAMPUS, TRICAP, or VA’’). ‘‘In general, how would you describe your own health?’’ (5 ¼ excellent, 4 ¼ very good, 3 ¼ good, 2 ¼ only fair, 2 ¼ poor) measured subjective health status. ‘‘What is the last grade or class you completed in school?’’ represented educational attainment. Responses were recoded into years of education (top-coded at 19). Annual household income was measured in 10 categories and then recoded into dollars (top-coded at $100,000). Gender was coded 1 for female and 0 for male. Age was measured in years (top-coded at 97). Analytic strategy After conducting univariate, bivariate and missing data analyses, I estimated multivariate logistic regression models assessing the relationships between perceived medical errors and patient–physician racial/ethnic concordance. To prevent potential bias, I controlled for correlates of perceived medical errors that are also related to the main explanatory variable, physician–patient racial/ethnic concordance. Control variables included the usual place of care, education, income, insurance status, and subjective health. Since physician–patient communication relates to racial/ethnic concordance (Garcia et al., 2003) as well as to perceptions of adverse events (Beckman, Markakis, Suchman, & Frankel, 1994), it was also included among control variables. To see whether the examined relationships vary among patients of different racial/ethnic/language backgrounds, I performed the analyses separately for each racial/ethnic/language group. To represent the population of the United States, I applied probability weights and adjusted for stratification
and clustering by telephone areas using Stata 8.0 statistical software. Results Univariate and bivariate statistics by racial/ ethnic/language groups appear in Table 1. On average, one in 10 respondents reported having experienced medical errors personally or in their families. The probabilities of reporting medical errors were similar across racial/ethnic/language groups, except for Hispanics interviewed in Spanish, who were less likely to report medical errors than Whites. Compared to White patients, minority patients were less likely to see a physician of a matching racial/ethnic background, have health insurance, and receive their care in doctors’ offices or private clinics. They were also younger than White patients. Hispanics were more likely than Whites to leave physicians’ offices with unanswered questions. Hispanics interviewed in Spanish and non-Black, non-Hispanic minority patients rated their physicians’ listening skills less favorably than Whites. Blacks and Hispanics interviewed in Spanish reported poorer health than Whites. Blacks and Hispanics reported lower income and education than Whites. Non-Black, non-Hispanic minority respondents, however, reported higher education than Whites. Table 2 displays the results of multivariate logistic regression models for each racial/ethnic/language group. The hypothesis that patients in racially/ ethnically concordant patient–physician relationships are less likely to report medical errors is supported only for White patients. White patients treated by White physicians have 33% lower odds of reporting a medical error than White patients treated by non-White physicians (po:05). Racial/ethnic concordance is not associated with perceived medical errors among minority patients. Among the control variables, physicians’ good listening skills are negatively associated with perceived medical errors among non-Hispanic, nonBlack patients. For Hispanics interviewed in English, the usual receipt of care in a physician’s office or a private clinic is positively associated with perceived medical errors. Perceived medical errors are negatively associated with subjective health among Blacks and Whites. They are positively associated with family income among non-Hispanic minorities. For Hispanics interviewed in Spanish, perceived medical errors have an inverted U-shaped
64;74
69 45 2.96 (.09) 54 38.41 (1.31) 1.16 (.35) 25.71 (2.15)
45
3.12 (.11) 28
21.49;29.93
9.47;1.84
44;64 35.83;1.99
35;55 2.79;3.13
35;55
3.19;3.38
2.92;3.3
18 3.49 (.07) 62 39.37 (1.02) 12.68 (.18) 4.73 (2.11)
77
3.46 (.05) 16
15
8
Estimate
36.58;44.87
12.33;13.04
55;69 37.35;41.38
13;22 3.35;3.62
71;81
3.12;3.21
3.36;3.55
10;19
5;12
CI
Hispanic, English interview (N ¼ 534)
11 3.42 (.10) 58 4.63 (1.18) 14.72 (.23) 55.46 (2.58)
74
3.36* (.07) 17
24
13
Estimate
5.39;6.51
14.26;15.18
50;66 38.32;42.95
5;16 3.23;3.61
68;81
3.11;3.24
3.24;3.49
18;30
8;19
CI
Other non-White (N ¼ 464)
9 3.58 (.03) 56 45.84 (.46) 13.74 (.07) 5.54 (8.58)
82
3.56 (.02) 11
70
10
Estimate
48.85;52.21
13.59;13.88
54;59 44.93;46.74
8;11 3.52;3.64
80;85
3.09;3.13
3.52;3.60
68;73
9;12
CI
Non-Hispanic White (N ¼ 2475)
Source: 2001 Survey on Disparities in Quality of Health Care. Notes: CI ¼ 95% confidence interval. UPC ¼ usual place of care. SE ¼ standard error of the mean. Standard errors appear in parentheses. a The variable is treated as continuous. b Top-coded at 97 years. c Top-coded at 19 years. d Top-coded at $100,000. y Wald statistic for Pearson chi-squared test for independence comparing respondents who reported medical errors to those who did not, corrected for the survey design. y t-test for differences in means comparing respondents in each minority group to Whites, corrected for the survey design. po:05: po:01: po:001:
34.16;39.54
12.69;13.16
55;65 39.94;43.05
15;23 3.31;3.51
3.10;3.17
3.48;3.63
3.56 (.04) 14
15;22
19 17;31
1;7
4
7;13
10 24
CI
Estimate
CI
Estimate
19 3.41 (.05) 60 41.50 (.79) Education in yearsc (mean, 12.93 SE)y (.12) Annual family income in 36.85 d y $1,000s (mean, SE) (1.40)
Reported medical error (%)y Patient–physician racial/ ethnic concordance (%)y Physician’s listeninga (mean; SE)y Patient’s unanswered question (%)y UPC: Doctor’s office/ private clinic (%)y Uninsured (%)y Subjective health statusa (mean, SE)y Female (%)y Age in yearsb (mean, SE)y
Hispanic, Spanish interview (N ¼ 213)
Non-Hispanic Black (N ¼ 747)
Table 1 Univariate and bivariate characteristics of the final sample, corrected for survey design
I. Stepanikova / Social Science & Medicine 63 (2006) 3060–3066
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.44;2.32 .54;1.34 .46;3.14 .75;2.95 .50;2.33 .72;3.06 .39;.78 .93;1.18 1.00;1.00 .75;1.09 1.05;2.69 .00;2.55
1.01
.85 1.21
1.49
1.08 1.48 .55 1.05 1.00 .90 1.68
4.04E3
.46;57.30 1.01;.03 .54;3.41 1.19;5.53 .98;1.00 .55;1.18 .72;17.70 .00;.01
9.19E15
.00;1.40
.41;1.36 .10;5.01
.09;6.32
5.15 .09 1.36 2.56 .99 .81 3.58
.08
.75 .71
.77
Source: 2001 Survey on Disparities in Quality of Health Care. Notes: CI ¼ 95% confidence interval. UPC ¼ usual place of care. a The variable is treated as continuous. b Top-coded at 97 years. c Top-coded at 19 years. d Top-coded at $100,000. po:05: po:01: po:001:
Patient–physician racial/ ethnic concordance Physician’s listeninga Patient’s unanswered question UPC: Doctor’s office/ private clinic Uninsured Female Subjective health statusa Age in yearsb Age in yearsb squared Education in yearsc Annual family income in US dollard logged Intercept
CI
Odds ratio
Odds ratio
CI
Hispanic, Spanish interview (N ¼ 213)
Non-Hispanic Black (N ¼ 747)
.37
.00;816.32
.16;1.32 .48;3.91 .44;1.50 .84;1.19 1.00;1.00 .92;1.40 .51;1.29
1.03;7.85
2.84 .46 1.37 .82 1.00 1.00 1.13 .81
.43;1.29 .43;3.41
.58;6.92
CI
.74 1.21
2.00
Odds ratio
Hispanic, English interview (N ¼ 534)
.00
4.21 .39 .76 1.04 1.00 .89 2.62
.00;139.89
.71;24.87 .14;1.14 .41;1.43 .81;1.32 1.00;1.00 .72;1.10 1.05;6.52
.19;3.72
.22;.80 .31;3.76
.42 1.09 .84
.11;1.65
CI
.42
Odds ratio
Other non-White (N ¼ 464)
Table 2 Logistic regression of perceived medical errors by patients’ race/ethnicity/language. Odds ratios and confidence intervals
2.32
1.20 1.43 .83 1.07 1.00 .99 .85
1.59
.08;7.21
.64;2.23 .98;2.10 .70;1.00 1.00;1.14 1.00;1.00 .92;1.07 .66;1.09
.95;2.65
.47;.75 .53;1.81
.45;.99
.67 .59 .98
CI
Odds ratio
Non-Hispanic White (N ¼ 2475)
3064 I. Stepanikova / Social Science & Medicine 63 (2006) 3060–3066
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relationship with age, peaking at approximately 44 years of age. Discussion Previous research on race/ethnicity and perceived medical errors has been inconclusive. Studies failing to find racial/ethnic differences in perceived medical errors (i.e., The Kaiser Family Foundation, 2004) or showing that bivariate racial/ethnic differences dissipate in multivariate analysis (i.e., Adams & Boscarino, 2004) stand in contrast to evidence that minority patients receive less safe care compared to White patients (i.e., Coffey, Andrews, & Moy, 2005) and are more concerned about the safety of their health care (The Kaiser Family Foundation, 2004). This study contributes to the understanding of the role of race/ethnicity in patients’ perceptions of health care safety by showing that White patients treated by White doctors are less likely to report medical errors than White patients treated by nonWhite doctors. The likelihood of reporting medical errors among non-White patients, however, does not vary with patient–physician racial/ethnic concordance. As this study controlled for measures of physician–patient communication, it is unlikely that communication barriers that may be present in some racially/ethnically discordant patient–physician relationships confound these findings. Additionally, this study reveals that a relationship between physicians’ listening skills and perceived medical errors exists only for non-Black, nonHispanic patients, and that patients’ unanswered questions are not related to perceived medical errors for any racial/ethnic/language group. These findings refine conclusions of previous research that perceptions of medical errors decrease with good physician–patient communication by showing that such relationship may exist only in some, not in all, patient groups. What is the meaning of these findings? Is errorfree care more common among White patients treated by White doctors than among other patients? Are White patients of White doctors more commonly blinded to the poor quality of care? Are White patients more suspicious of physicians of differing racial/ethnic backgrounds? Do White patients who, for whatever reason, perceive their care as error-free tend to select White doctors? The limitations of the data used in this study prevent conclusively answering these questions. Since the data are cross-sectional, they cannot be used to
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examine causal relationships among variables. Further research, preferably with longitudinal data, must examine whether racial/ethnic concordance decreases perceptions of medical errors among White patients; whether White patients who are less likely to perceive medical errors select racially/ ethnically concordant physicians, or whether both these causal effects exist. Status characteristic theories (Berger, Cohen, & Zelditch, 1972; Ridgeway, 1997; Ridgeway & Balkwell, 1997) suggest how racial/ethnic concordance influences perceptions. According to these theories, social categories, such as race/ethnicity, are associated with culturally shared meanings about who members of these categories are and what their comparative status is in the society. Importantly, social categories are also associated with expectations for competence in task-oriented groups. In general, people expect persons of higher social status to be more competent than persons of lower social status. White patients have higher racial/ ethnic status than non-White doctors. Insofar as the physician–patient encounter is task-oriented, racial/ ethnic status differences may decrease expectations for physicians’ competence among White patients treated by non-White physicians. Patients may perceive medical mistakes as signs of lower physician’s competence. Once White patients expect their non-White doctors to be less competent, they may be relatively quick to ‘‘confirm’’ their expectations by attributing medical maloccurrences of any etiology to doctors’ mistakes. The finding that compared to White patients of White physicians, White patients of minority physicians are more likely to report medical errors is consistent with such arguments, since racial/ethnic status differences experienced by White patients of minority doctors may affect negatively patients’ expectations for doctors’ ability to deliver error-free care. Also consistent is the finding of no relationship between patient–physician racial/ethnic concordance and medical errors among minority patients and among Whites treated by Whites. White patients of White physicians and minority patients, who have lower or similar racial/ethnic status relative to their physicians (depending on whether their physician is White or minority), may be less likely to doubt their physicians’ competence to deliver error-free care. If medical maloccurrences happen, such patients may attribute them to other causes, not to a medical mistake. Future research applying status characteristic theories to patient–physician
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relationships could help to understand the dynamics of competence perceptions in racially/ethnically concordant and discordant patient–physician relationships. Additionally, future surveys could make a stronger contribution to the understanding of what perceived errors mean for reported errors if perceptions were distinguished from action. Such data could reveal the propensity of patients in racially/ ethnically concordant and discordant relationships to take action if they perceive errors in their health care. Importantly, these data could indicate when patients of different racial/ethnic backgrounds report such perceptions to their physicians or to other health care providers and when they take other, possibly more problematic, types of action, such as malpractice litigation. Acknowledgment I would like to thank The Commonwealth Fund for providing the data and Karen S. Cook for feedback on previous drafts of this paper.
References Adams, R. E., & Boscarino, J. A. (2004). A community survey of medical errors in New York. International Journal of Quality in Health Care, 16(5), 353–362. Beckman, H. B., Markakis, K. M., Suchman, A. L., & Frankel, R. M. (1994). The doctor–patient relationship and malpractice. Lessons from plaintiff depositions. Archives of Internal Medicine, 154(12), 1365–1370. Berger, J., Cohen, B. P., & Zelditch, M. (1972). Status characteristics and social interaction. American Sociological Review, 37, 241–255.
Blendon, R. J., DesRoches, C. M., Brodie, M., et al. (2002). Views of the public and practicing physicians on medical errors. New England Journal of Medicine, 347, 1933–1940. Coffey, R. M., Andrews, R. M., & Moy, E. (2005). Racial, ethnic, and socioeconomic disparities in estimates of AHRQ patient safety indicators. Medical Care, 43(Suppl), I-48–I-57. Cooper-Patrick, L., Gallo, J. J., Gonzales, J. J., et al. (1999). Race, gender, and partnership in the patient–physician relationship. JAMA, 282(6), 583–589. Garcia, J. A., Paterniti, D. A., Romano, P. S., & Kravitz, R. L. (2003). Patient preferences for physician characteristics in university-based primary care clinics. Ethnicity and Disease, 13(2), 259–267. Institute of Medicine. (1999). To Err is Human: Building a Safer Health Care System. Washington, DC: National Academies Press. LaVeist, T. A., & Nuru-Jeter, A. (2002). Is doctor–patient race concordance associated with greater satisfaction with care? Journal of Health and Social Behavior, 43, 296–306. National Patient Safety Foundation at the AMA. (1997). Public opinion of patient safety research findings. Available at: /http://www.npsf.org/download/1997survey.pdfS. Accessed March 20, 2005. Ridgeway, C. L. (1997). Interaction and the conservation of gender inequality. American Sociological Review, 62, 218–235. Ridgeway, C. L., & Balkwell, J. W. (1997). Processes and the diffusion of status beliefs. Social Psychology Quarterly, 60(1), 14–31. Saha, S., Komaromy, M., Koepsell, T. D., & Bindman, A. B. (1999). Patient–physician racial concordance and the perceived quality and use of health care. Archives of Internal Medicine, 159(9), 997–1004. Starfield, B. (2000). Is US health really the best in the world? JAMA, 284, 483–485. The Kaiser Family Foundation. (2004). National survey on consumers’ experiences with patient safety and quality information. Available at: /http://www.kff.org/kaiserpolls/ pomr111704pkg.cfm.S Accessed March 20, 2005. von Laue, N. C., Schwappach, D. L., & Koeck, C. M. (2003). The epidemiology of medical errors: A review of the literature. Wien Klin Wochenschr, 115(10), 318–325. Weingart, S. N., Wilson, R. M., Gibberd, R. W., & Harrison, B. (2000). Epidemiology and medical error. BMJ, 320, 774–777.
Social Science & Medicine 63 (2006) 3060–3066 www.elsevier.com/locate/socscimed
Patient–physician racial and ethnic concordance and perceived medical errors Irena Stepanikova University of South Carolina, Columbia, SC, USA Available online 22 September 2006
Abstract In this paper, I use nationally representative survey data to examine the relationship between patient–physician racial/ ethnic concordance and perceived medical errors in the USA. After adjusting for potential confounding factors, we find that White patients treated by White physicians have 33% lower odds of reporting medical errors than White patients treated by non-White physicians. In contrast, patient–physician racial/ethnic concordance has no effect on perceived medical errors among non-White patients. The results suggest that the role of racial/ethnic concordance in perceptions of health care safety varies by patients’ racial/ethnic background. r 2006 Elsevier Ltd. All rights reserved. Keywords: Perceived medical errors; Race/ethnicity; USA; Patients
Main text Medical errors represent a serious threat to patient safety. Deaths resulting from medical errors in the United States range from 44,000 to 98,000 annually, exceeding those resulting from AIDS or motor vehicle accidents (Institute of Medicine, 1999). A more recent estimate of 225,000 deaths from errors and adverse effects makes iatrogenic events the third leading cause of death, exceeded only by heart disease and cancer (Starfield, 2000). The incidences of adverse events range between 3% and 17% of all hospitalizations (von Laue, Schwappach, & Koeck, 2003). In outpatient care, errors occur in 4–18% of visits (Weingart, Wilson, Gibberd, & Harrison, 2000). The estimated national costs of preventable adverse events range between Tel.: +1 803 777 6866.
E-mail address: [email protected]. 0277-9536/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.socscimed.2006.08.015
17 and 29 billion annually (Institute of Medicine, 1999). Many Americans are concerned about medical errors. Thirty-three percent (National Patient Safety Foundation, 1997) to 42% (Blendon, DesRoches, & Brodie, 2002) of respondents to national surveys report having experienced medical errors either personally or in their families. Respondents often associate these errors with serious consequences, including severe pain, loss of time at work or school, disability, and death (The Kaiser Family Foundation, 2004). Forty-seven percent of American adults disagree that the current health care system has adequate measures in place to prevent medical mistakes (National Patient Safety Foundation, 1997). The purpose of this study is to explore whether patient–physician racial/ethnic concordance, i.e., the match between the physician’s and the patient’s racial/ethnic backgrounds, is related to patients’
ARTICLE IN PRESS I. Stepanikova / Social Science & Medicine 63 (2006) 3060–3066
perceptions of medical errors. Research on patient safety has neglected this issue but we know that the lack of patient–physician racial/ethnic concordance is associated with worse health care outcomes, including lower patient satisfaction (LaVeist & Nuru-Jeter, 2002; Saha, Komaromy, Koepsell, & Bindman, 1999) and less participation in medical decision-making (Cooper-Patrick, Gallo, & Gonzales, 1999). Some minority patients believe that the lack of racial/ethnic concordance leads to worse physician–patient communication and decreases physicians’ empathy (Garcia, Paterniti, Romano, & Kravitz, 2003). How might patient–physician racial/ethnic concordance relate to patients’ perceptions of medical errors? I propose two parallel mechanisms. First, racial/ethnic concordance may decrease the likelihood that medical errors occur and hereby decrease patients’ perceptions of errors. Crosscultural and language barriers in racially/ethnically discordant relationships may make it difficult for physicians to obtain complete and accurate information from patients and may eventually lead to more frequent errors in the diagnosis and treatment. Second, patient–physician racial/ethnic concordance may reduce patients’ perceptions of medical errors, whether or not the errors actually occurred. Racial/ethnic concordance contributes to well-functioning, trustful patient–physician relationships. Patients treated by physicians of the same racial/ ethnic background, who enjoy trustful relationships, may be less likely to causally attribute adverse events or other types of negative experiences with the health care process and outcomes to their physicians’ negligence or error. These arguments lead me to hypothesize that patients in racially/ ethnically concordant patient– physician relationships are less likely to report medical errors than other patients. Data 2001 Survey on Disparities in Quality of Health Care, sponsored by The Commonwealth Fund, is a random-digit-dial telephone survey with 6722 adults (age 18 and older) residing in the continental United States. Telephone numbers from areas with a higher than average density of minority residents were over-sampled. Respondents reported their sources of, access to, and utilization of health care; experiences with health care; and socio-demographic characteristics. Since only respondents
3061
who reported having a regular physician and who saw a physician in the last year were asked about the physician’s race/ethnicity and about physician–patient communication, the analyses necessarily exclude respondents with no regular physician and those who have not recently received any health care. The final non-missing N after these exclusions is 4385. Data are missing randomly on the dependent variable.
Measures Respondents were asked, ‘‘Have you or any family member ever gotten sick or gotten worse as a result of going to the doctor’s office or being hospitalized?’’ Those who answered in the affirmative were asked, ‘‘Do you think this was due to a mistake made at the doctor’s office or hospital?’’ Perceived medical errors were coded as 1 for respondents who answered yes to both these questions and 0 for all others. Respondents’ reported their ethnicity (Hispanic or non-Hispanic) and race (White, Black, Asian, Native American, and Pacific Islander). Due to the small number of respondents, I collapse the last three racial categories into a single category, ‘‘other’’. To approximate English proficiency, I further distinguish between Hispanics who chose a Spanish interview and Hispanics who chose an English interview. Resulting categories for race/ethnicity/language are non-Hispanic Black, non-Hispanic White, Hispanic interviewed in Spanish, Hispanic interviewed in English, and other. Respondents also reported their regular physician’s race/ethnicity.1 Patient– physician racial/ethnic concordance was coded as 1 if the patient’s and physician’s race/ethnicity matched and 0 otherwise. Two aspects of physician–patient communication were measured. ‘‘The last time you visited a doctor, did the doctor listen to everything you had to say, to most, to some, or only a little of what you had to say?’’ (4 ¼ everything, 3 ¼ most, 2 ¼ some, 1 ¼ only a little) represented physicians’ listening skills. ‘‘Did you have questions about your care or treatment that you wanted to discuss but did not?’’ 1
To determine whether respondents have a regular source of care, they were asked: ‘‘Do you have a regular doctor or other health professional, such as a nurse or a midwife, you usually go to when you are sick or need health care?’’.
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(1 ¼ yes, 0 ¼ no) represented patients’ unanswered questions. For the place where care is usually delivered, respondents were asked, ‘‘Where do you usually go when you are sick or need health care?’’ ‘‘Doctor’s office or private clinic’’ was coded as 1. All other responses, including ‘‘community health center or other public clinic’’, ‘‘hospital outpatient department’’, ‘‘hospital emergency room’’, or ‘‘some other place’’, were coded as 0. For the insurance status, uninsured respondents are distinguished from respondents with health insurance (‘‘health insurance through your or someone else’s employer or work or health insurance bought directly by you or your family’’, ‘‘Medicaid’’; ‘‘Medicare’’; or ‘‘other government or state medical program such a CHAMPUS, TRICAP, or VA’’). ‘‘In general, how would you describe your own health?’’ (5 ¼ excellent, 4 ¼ very good, 3 ¼ good, 2 ¼ only fair, 2 ¼ poor) measured subjective health status. ‘‘What is the last grade or class you completed in school?’’ represented educational attainment. Responses were recoded into years of education (top-coded at 19). Annual household income was measured in 10 categories and then recoded into dollars (top-coded at $100,000). Gender was coded 1 for female and 0 for male. Age was measured in years (top-coded at 97). Analytic strategy After conducting univariate, bivariate and missing data analyses, I estimated multivariate logistic regression models assessing the relationships between perceived medical errors and patient–physician racial/ethnic concordance. To prevent potential bias, I controlled for correlates of perceived medical errors that are also related to the main explanatory variable, physician–patient racial/ethnic concordance. Control variables included the usual place of care, education, income, insurance status, and subjective health. Since physician–patient communication relates to racial/ethnic concordance (Garcia et al., 2003) as well as to perceptions of adverse events (Beckman, Markakis, Suchman, & Frankel, 1994), it was also included among control variables. To see whether the examined relationships vary among patients of different racial/ethnic/language backgrounds, I performed the analyses separately for each racial/ethnic/language group. To represent the population of the United States, I applied probability weights and adjusted for stratification
and clustering by telephone areas using Stata 8.0 statistical software. Results Univariate and bivariate statistics by racial/ ethnic/language groups appear in Table 1. On average, one in 10 respondents reported having experienced medical errors personally or in their families. The probabilities of reporting medical errors were similar across racial/ethnic/language groups, except for Hispanics interviewed in Spanish, who were less likely to report medical errors than Whites. Compared to White patients, minority patients were less likely to see a physician of a matching racial/ethnic background, have health insurance, and receive their care in doctors’ offices or private clinics. They were also younger than White patients. Hispanics were more likely than Whites to leave physicians’ offices with unanswered questions. Hispanics interviewed in Spanish and non-Black, non-Hispanic minority patients rated their physicians’ listening skills less favorably than Whites. Blacks and Hispanics interviewed in Spanish reported poorer health than Whites. Blacks and Hispanics reported lower income and education than Whites. Non-Black, non-Hispanic minority respondents, however, reported higher education than Whites. Table 2 displays the results of multivariate logistic regression models for each racial/ethnic/language group. The hypothesis that patients in racially/ ethnically concordant patient–physician relationships are less likely to report medical errors is supported only for White patients. White patients treated by White physicians have 33% lower odds of reporting a medical error than White patients treated by non-White physicians (po:05). Racial/ethnic concordance is not associated with perceived medical errors among minority patients. Among the control variables, physicians’ good listening skills are negatively associated with perceived medical errors among non-Hispanic, nonBlack patients. For Hispanics interviewed in English, the usual receipt of care in a physician’s office or a private clinic is positively associated with perceived medical errors. Perceived medical errors are negatively associated with subjective health among Blacks and Whites. They are positively associated with family income among non-Hispanic minorities. For Hispanics interviewed in Spanish, perceived medical errors have an inverted U-shaped
64;74
69 45 2.96 (.09) 54 38.41 (1.31) 1.16 (.35) 25.71 (2.15)
45
3.12 (.11) 28
21.49;29.93
9.47;1.84
44;64 35.83;1.99
35;55 2.79;3.13
35;55
3.19;3.38
2.92;3.3
18 3.49 (.07) 62 39.37 (1.02) 12.68 (.18) 4.73 (2.11)
77
3.46 (.05) 16
15
8
Estimate
36.58;44.87
12.33;13.04
55;69 37.35;41.38
13;22 3.35;3.62
71;81
3.12;3.21
3.36;3.55
10;19
5;12
CI
Hispanic, English interview (N ¼ 534)
11 3.42 (.10) 58 4.63 (1.18) 14.72 (.23) 55.46 (2.58)
74
3.36* (.07) 17
24
13
Estimate
5.39;6.51
14.26;15.18
50;66 38.32;42.95
5;16 3.23;3.61
68;81
3.11;3.24
3.24;3.49
18;30
8;19
CI
Other non-White (N ¼ 464)
9 3.58 (.03) 56 45.84 (.46) 13.74 (.07) 5.54 (8.58)
82
3.56 (.02) 11
70
10
Estimate
48.85;52.21
13.59;13.88
54;59 44.93;46.74
8;11 3.52;3.64
80;85
3.09;3.13
3.52;3.60
68;73
9;12
CI
Non-Hispanic White (N ¼ 2475)
Source: 2001 Survey on Disparities in Quality of Health Care. Notes: CI ¼ 95% confidence interval. UPC ¼ usual place of care. SE ¼ standard error of the mean. Standard errors appear in parentheses. a The variable is treated as continuous. b Top-coded at 97 years. c Top-coded at 19 years. d Top-coded at $100,000. y Wald statistic for Pearson chi-squared test for independence comparing respondents who reported medical errors to those who did not, corrected for the survey design. y t-test for differences in means comparing respondents in each minority group to Whites, corrected for the survey design. po:05: po:01: po:001:
34.16;39.54
12.69;13.16
55;65 39.94;43.05
15;23 3.31;3.51
3.10;3.17
3.48;3.63
3.56 (.04) 14
15;22
19 17;31
1;7
4
7;13
10 24
CI
Estimate
CI
Estimate
19 3.41 (.05) 60 41.50 (.79) Education in yearsc (mean, 12.93 SE)y (.12) Annual family income in 36.85 d y $1,000s (mean, SE) (1.40)
Reported medical error (%)y Patient–physician racial/ ethnic concordance (%)y Physician’s listeninga (mean; SE)y Patient’s unanswered question (%)y UPC: Doctor’s office/ private clinic (%)y Uninsured (%)y Subjective health statusa (mean, SE)y Female (%)y Age in yearsb (mean, SE)y
Hispanic, Spanish interview (N ¼ 213)
Non-Hispanic Black (N ¼ 747)
Table 1 Univariate and bivariate characteristics of the final sample, corrected for survey design
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.44;2.32 .54;1.34 .46;3.14 .75;2.95 .50;2.33 .72;3.06 .39;.78 .93;1.18 1.00;1.00 .75;1.09 1.05;2.69 .00;2.55
1.01
.85 1.21
1.49
1.08 1.48 .55 1.05 1.00 .90 1.68
4.04E3
.46;57.30 1.01;.03 .54;3.41 1.19;5.53 .98;1.00 .55;1.18 .72;17.70 .00;.01
9.19E15
.00;1.40
.41;1.36 .10;5.01
.09;6.32
5.15 .09 1.36 2.56 .99 .81 3.58
.08
.75 .71
.77
Source: 2001 Survey on Disparities in Quality of Health Care. Notes: CI ¼ 95% confidence interval. UPC ¼ usual place of care. a The variable is treated as continuous. b Top-coded at 97 years. c Top-coded at 19 years. d Top-coded at $100,000. po:05: po:01: po:001:
Patient–physician racial/ ethnic concordance Physician’s listeninga Patient’s unanswered question UPC: Doctor’s office/ private clinic Uninsured Female Subjective health statusa Age in yearsb Age in yearsb squared Education in yearsc Annual family income in US dollard logged Intercept
CI
Odds ratio
Odds ratio
CI
Hispanic, Spanish interview (N ¼ 213)
Non-Hispanic Black (N ¼ 747)
.37
.00;816.32
.16;1.32 .48;3.91 .44;1.50 .84;1.19 1.00;1.00 .92;1.40 .51;1.29
1.03;7.85
2.84 .46 1.37 .82 1.00 1.00 1.13 .81
.43;1.29 .43;3.41
.58;6.92
CI
.74 1.21
2.00
Odds ratio
Hispanic, English interview (N ¼ 534)
.00
4.21 .39 .76 1.04 1.00 .89 2.62
.00;139.89
.71;24.87 .14;1.14 .41;1.43 .81;1.32 1.00;1.00 .72;1.10 1.05;6.52
.19;3.72
.22;.80 .31;3.76
.42 1.09 .84
.11;1.65
CI
.42
Odds ratio
Other non-White (N ¼ 464)
Table 2 Logistic regression of perceived medical errors by patients’ race/ethnicity/language. Odds ratios and confidence intervals
2.32
1.20 1.43 .83 1.07 1.00 .99 .85
1.59
.08;7.21
.64;2.23 .98;2.10 .70;1.00 1.00;1.14 1.00;1.00 .92;1.07 .66;1.09
.95;2.65
.47;.75 .53;1.81
.45;.99
.67 .59 .98
CI
Odds ratio
Non-Hispanic White (N ¼ 2475)
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relationship with age, peaking at approximately 44 years of age. Discussion Previous research on race/ethnicity and perceived medical errors has been inconclusive. Studies failing to find racial/ethnic differences in perceived medical errors (i.e., The Kaiser Family Foundation, 2004) or showing that bivariate racial/ethnic differences dissipate in multivariate analysis (i.e., Adams & Boscarino, 2004) stand in contrast to evidence that minority patients receive less safe care compared to White patients (i.e., Coffey, Andrews, & Moy, 2005) and are more concerned about the safety of their health care (The Kaiser Family Foundation, 2004). This study contributes to the understanding of the role of race/ethnicity in patients’ perceptions of health care safety by showing that White patients treated by White doctors are less likely to report medical errors than White patients treated by nonWhite doctors. The likelihood of reporting medical errors among non-White patients, however, does not vary with patient–physician racial/ethnic concordance. As this study controlled for measures of physician–patient communication, it is unlikely that communication barriers that may be present in some racially/ethnically discordant patient–physician relationships confound these findings. Additionally, this study reveals that a relationship between physicians’ listening skills and perceived medical errors exists only for non-Black, nonHispanic patients, and that patients’ unanswered questions are not related to perceived medical errors for any racial/ethnic/language group. These findings refine conclusions of previous research that perceptions of medical errors decrease with good physician–patient communication by showing that such relationship may exist only in some, not in all, patient groups. What is the meaning of these findings? Is errorfree care more common among White patients treated by White doctors than among other patients? Are White patients of White doctors more commonly blinded to the poor quality of care? Are White patients more suspicious of physicians of differing racial/ethnic backgrounds? Do White patients who, for whatever reason, perceive their care as error-free tend to select White doctors? The limitations of the data used in this study prevent conclusively answering these questions. Since the data are cross-sectional, they cannot be used to
3065
examine causal relationships among variables. Further research, preferably with longitudinal data, must examine whether racial/ethnic concordance decreases perceptions of medical errors among White patients; whether White patients who are less likely to perceive medical errors select racially/ ethnically concordant physicians, or whether both these causal effects exist. Status characteristic theories (Berger, Cohen, & Zelditch, 1972; Ridgeway, 1997; Ridgeway & Balkwell, 1997) suggest how racial/ethnic concordance influences perceptions. According to these theories, social categories, such as race/ethnicity, are associated with culturally shared meanings about who members of these categories are and what their comparative status is in the society. Importantly, social categories are also associated with expectations for competence in task-oriented groups. In general, people expect persons of higher social status to be more competent than persons of lower social status. White patients have higher racial/ ethnic status than non-White doctors. Insofar as the physician–patient encounter is task-oriented, racial/ ethnic status differences may decrease expectations for physicians’ competence among White patients treated by non-White physicians. Patients may perceive medical mistakes as signs of lower physician’s competence. Once White patients expect their non-White doctors to be less competent, they may be relatively quick to ‘‘confirm’’ their expectations by attributing medical maloccurrences of any etiology to doctors’ mistakes. The finding that compared to White patients of White physicians, White patients of minority physicians are more likely to report medical errors is consistent with such arguments, since racial/ethnic status differences experienced by White patients of minority doctors may affect negatively patients’ expectations for doctors’ ability to deliver error-free care. Also consistent is the finding of no relationship between patient–physician racial/ethnic concordance and medical errors among minority patients and among Whites treated by Whites. White patients of White physicians and minority patients, who have lower or similar racial/ethnic status relative to their physicians (depending on whether their physician is White or minority), may be less likely to doubt their physicians’ competence to deliver error-free care. If medical maloccurrences happen, such patients may attribute them to other causes, not to a medical mistake. Future research applying status characteristic theories to patient–physician
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relationships could help to understand the dynamics of competence perceptions in racially/ethnically concordant and discordant patient–physician relationships. Additionally, future surveys could make a stronger contribution to the understanding of what perceived errors mean for reported errors if perceptions were distinguished from action. Such data could reveal the propensity of patients in racially/ ethnically concordant and discordant relationships to take action if they perceive errors in their health care. Importantly, these data could indicate when patients of different racial/ethnic backgrounds report such perceptions to their physicians or to other health care providers and when they take other, possibly more problematic, types of action, such as malpractice litigation. Acknowledgment I would like to thank The Commonwealth Fund for providing the data and Karen S. Cook for feedback on previous drafts of this paper.
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