Family Practice Advance Access originally published online on February 27, 2008
Family Practice 2008 25(1):49-55; doi:10.1093/fampra/cmn005
Effect of race on patient expectations regarding their primary care physicians
a Division of General Internal Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA
b The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA
c Center for Health Equity Research and Promotion, Philadelphia Veterans Affairs Medical, Philadelphia, PA, USA
Correspondence to Carmen E. Guerra, University of Pennsylvania, 1221 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA; Email: carmen.guerra{at}uphs.upenn.edu. Karima Ravenell is currently at the University of Texas at Southwestern Medical Center, Dallas, TX, USA.
Received 23 March 2007; Revised 21 December 2007; Accepted 9 January 2008.
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionDeclarationReferences |
|---|
Background. Fulfilment of patients’ expectations has been associated with greater patient satisfaction with care and greater adherence to medical advice. However, little is know about how race influences patient expectations.
Objective. To determine the association between patient race and patient expectations of their primary care physician.
Methods. The design was a cross-sectional study. Setting and participants were sample of 709 primary care patients from four clinic sites at the Philadelphia Veterans Affairs Medical Center and the University of Pennsylvania Health System. The measures were an expectations instrument asking patients to rate the necessity of the physician performing 13 activities during the index visit, self-reported race, demographics, the Rapid Estimate of Adult Literacy in Medicine, the Charlson Comorbidity Index and SF-12.
Results. After adjusting for age, sex, education, clinic site, comorbidity, health literacy and health status, African Americans were more likely to report it was absolutely necessary for the physician to refer them to a specialist [AOR 1.55 (95% confidence interval, CI, 1.09–2.21), P = 0.01], order tests [AOR 1.59 (95% CI 1.11–2.27), P = 0.01] and conduct each of the six physical exam components.
Conclusions. African American race is associated with greater expectations of the primary care physicians. More research is needed to confirm the differential expectations by race and determine the reasons for the differential expectations.
Keywords. Communication, expectations, health literacy, patient–physician relationships, race.
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionDeclarationReferences |
|---|
Patient expectations, defined as what patients perceive to be necessary,1 are being increasingly recognized as important factors to patients, providers and policy makers. Patient expectations have been shown to influence providers’ prescribing behaviors2 and decisions to order cancer screening tests.3 Fulfilment of patients’ expectations is associated with greater patient satisfaction with care,4–11 greater adherence to medical advice12,13 and some disease outcomes.7 Conversely, unmet expectations are associated with lower patient satisfaction, lower intention to adhere to treatment and more post-visit health system contacts.14 Despite the importance of expectations, studies have shown that 18% of patients attending outpatient appointments have at least one unmet expectation.15 Most unmet expectations are perceived by patients to be omissions of care such as not receiving a prescription for medication or a referral to a specialist.15 As medicine has shifted to a patient-centred paradigm, fulfilment of patient expectations is increasingly being viewed as a measure of health care quality.16
Previous research examining the association between race and expectations is limited and shows conflicting results. Two studies in the US demonstrated that compared to whites, non-whites report more expectations.5,17 Another study compared the expectations of a multi-racial group of patients attending a primary care clinic in London and found that Vietnamese patients had lower expectations of their visit compared to the white and black patients.18 These few and conflicting studies of race and expectations call for additional understanding of the association between patient race and health care expectations. Furthermore, if primary care physicians are to successfully manage the expectations of the consumers they serve, it is important for them to understand how health expectations may differ between racial groups.
The objective of this study was to examine the association between patient race and patient expectations of their primary care physicians. Based on the earlier studies,5,17 our hypothesis was that, compared to whites, African Americans would have greater expectations of primary care providers. We adjusted for various confounders that have been demonstrated to be associated with patient race and expectations including health status,15 education19 and health literacy.20
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionDeclarationReferences |
|---|
This cross-sectional study is part of a larger study involving the development of a patient satisfaction instrument for populations with limited literacy.21 A convenience sample of patients waiting for appointments with a primary care provider at the Philadelphia Veterans Affairs Medical Center (VAMC) and the University of Pennsylvania Health System (UPHS) between May 2001 and April 2002 were invited to participate. Both the VAMC and UPHS clinics draw from patient populations that are racially and economically diverse, though both have a majority African American and low-income population. Patients were eligible if they were over the age of 18 years and spoke English.
Measures
Patient race was obtained via self-report. Patient expectations were assessed using a modified version of the long instrument used by Peck et al.1 This modified instrument asks ‘Do you think it is necessary for the doctor to: be familiar with your medical records; ask how your condition is affecting your life and family; ask about your personal health habits; ask about previous treatments you've tried for your condition; prescribe new medication and refer you to a specialist'. The instrument also asks whether it is necessary for the doctor to perform several physical examination components: examine eyes, nose and/or throat; listen to lungs and heart with stethoscope; check the abdomen for tenderness or organ enlargement; perform a rectal exam and perform a careful physical exam. The instrument also asks seven specific tests physicians might order (cholesterol, EKG, exercise stress test, PSA, blood, X-ray or scan and urine tests) which were each condensed into a single entry ‘order tests'. Response choices were ‘absolutely necessary', ‘somewhat necessary', ‘somewhat unnecessary’ or ‘absolutely unnecessary'.
Patients also completed the Charlson Comorbidity Index,22 which has been found to predict mortality risk over a period of a few weeks to 10 years in a variety of conditions.23–26 Although the Charlson Comorbidity Index was initially derived as a prognostic measure to study comorbidity in inpatients, it has been used to evaluate chronic disease in outpatients.27,28 Furthermore, the Charlson Index has been previously used in African Americans.29,30
Participants were also administered the Rapid Estimate of Adult Literacy in Medicine (REALM), a measure of medical word pronunciation that has been used as a proxy for health literacy.31 Studies have demonstrated that the REALM compares favourably to other formal reading assessments and has excellent test–retest reliability.32 The REALM has been found to be a robust measure of reading skills in African Americans and white patients.33
Several weeks into the study, the SF-12 was added to the parent study packet. The SF-1234 is a generic, 12-item health survey that captures health-related quality of life in eight constructs: physical functioning, role limitations due to physical problems, bodily pain, general health perceptions vitality, which together make up the physical component summary (PCS-12) scale and social functioning, role limitations due to emotional problems and mental health which make up the mental component summary (MCS-12) scale. The two scales have general population norm-based means of 50 and a SD of 10. Lower scores indicate poorer health status.35 The SF-12 has excellent test–retest reliability and criterion validity.34–36
A research assistant elicited demographic information and administered the REALM. Subjects self-administered all other instruments with the assistant available to administer the instruments for subjects that required it. Study participants were offered either a duffel bag with their respective clinic site logo or a $10.00 gift certificate to a local supermarket. This study was approved by the Institutional Review Board of the University of Pennsylvania.
Statistical analysis
All analyses were conducted with Statistical Analysis System, Version 9.1.37 To facilitate interpretation, expectations were dichotomized to compare absolutely necessary responses versus somewhat necessary, somewhat unnecessary and absolutely unnecessary for their primary care provider to perform. Chi-square analyses and analyses of variance were used to compare race (African American versus white) to demographic characteristics including age, education, sex, clinic site and race and to number of comorbidities (0, 1, 2, >3) and SF-12 scores.
The 13 expectation items were analysed as separate dependent variables in bivariate and multivariate logistic regression models (shown in Table 2). The six physical exam items were also combined into a single indicator. This combined physical exam indicator was dichotomized to compare those who marked absolutely necessary for 75% or more of the six physical exam items to those who marked absolutely necessary to fewer than 75% of the items to determine whether there was an association between race and expectations for a complete physical exam, making the assumption that five or six of the physical exam components were a proxy for a complete exam.
|
Logistic regressions adjusted for sociodemographic characteristics, clinic site, REALM grade reading level and comorbidity. Interaction terms for race and education, race and REALM score and race and sex were also entered in the model. Analyses were run with and without health status in the model, due to the late introduction of the SF-12 to the study protocol (denoted by ‘c’ in the Table 2).
|
Eighty-five per cent of the patients approached consented to participating in the study. Demographic data are not available for non-participants. A total of 86 patients who self-described their race as other than African American or white and were excluded from the analysis as the numbers were too small for meaningful comparisons.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionDeclarationReferences |
|---|
Table 1 shows the participant characteristics. A total of 709 patients completed the pertinent instruments and self-identified their race as African American (67%) or white (33%). The mean age (SD) of the participants was 51.7 (14.0) and the majority were male (61%). The majority of the sample had at least a high school degree (90%). Almost two-thirds of the patients (61%) were recruited from the VA clinics. REALM scores showed that 40% of the sample read at less than an eighth grade level. A total of 62% of the sample reported no comorbidities. MCS-12 and PCS-12 scores (SD) for the overall sample were 45.9 (11.7) and 40.7 (11.6) which represents lower perceived health status when compared to the general population norms of 50 (10). When the sample was stratified by race, African Americans were more likely to be female (P < 0.0001), have less education (P < 0.0001), more likely to obtain their care at the VA (P < 0.0001) and have lower health literacy scores (P < 0.0001).
Table 2 shows the bivariate and multivariate models examining the relationships between race and expectations. In bivariate models, compared to whites, African Americans were more likely to believe it is absolutely necessary for the doctor to be familiar with their medical records [odds ratio (OR) 1.60 (95% confidence interval, CI, 1.13–2.26), P = 0.008], prescribe a new medication [OR 1.50, (95% CI 1.08–2.10), P = 0.02], refer to a specialist [OR 1.56 (95% CI 1.13–2.17), P = 0.008], order tests [OR 1.50 (95% CI 1.08–2.08), P = 0.02] and perform all six physical exam components. In addition, compared to whites, African Americans were more likely to expect that doctor to conduct at least three-quarters of the physical exam components [OR 2.08 (95% CI 1.51–2.88), P < 0.0001] indicating African Americans were more likely to expect a complete physical exam.
In multivariate logistic regression models, after adjusting for age, sex, education, clinic site, REALM score and comorbidity and three interaction terms (race * REALM score, race * education and race * sex), compared to whites, African Americans were more likely to report it was absolutely necessary for the physician to refer them to a specialist [AOR 1.55 (95% CI 1.09–2.21), P = 0.01], order tests [AOR 1.59 (95% CI 1.11–2.27), P = 0.01] and conduct each of the six physical exam components. African Americans were also more likely to believe it was absolutely necessary for the doctor to be familiar with their medical records [AOR 1.58 (95% CI 1.09–2.29), P = 0.02] and expect the physician to conduct at least 75% of the components of the physical exam [AOR 1.91 (95% CI 1.35–2.70), P = 0.003)], but these results were no longer significant when health status (available for only 84% of the sample) was added to the model (‘c’ in Table 2). There was no statistically significant interaction between race and education and race and REALM score. The interaction between race and sex was significant for asking about health habits, referring to a specialist and ordering tests. In all three cases, white women men had greater expectations than white women. Black men had slightly greater expectations than black women.
In general, there were few statistically significant associations between expectations and other covariates in the model (age, education, sex, clinic site, literacy and comorbidity). Covariates related to two or more of the 13 items include age which was inversely associated with the opinion that it is necessary for the doctor to ask about how the condition is affecting life and family, personal habits and treatments tried, but positively associated with the expectation that it is necessary for the doctor to examine the heart, abdomen and perform a rectal exam. Literacy was positively associated with greater expectations for being prescribed new medication, being referred to a specialist, and a rectal exam. VA clinic site was associated with greater expectation for the doctor to ask how the condition is affecting life and family and negatively associated with expectation of a lung exam (not shown in tables).
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionDeclarationReferences |
|---|
Consistent with other studies,5,17 we found that African-American patients reported higher ratings of expectations that physicians would perform a number of tasks. Specifically, after controlling for potential confounders including demographic characteristics, medical word pronunciation (as a proxy for health literacy), comorbidity and health status, African Americans attending primary care clinics were more likely to expect the provider to perform many of the actions listed on a 13-item expectations instrument. By individual physician action, African Americans were at least 50% more likely to expect the provider to refer to a specialist, order tests and perform each of the six physical exam actions. African Americans also expected physicians to be familiar with their records, but this did not meet statistical significance once we adjusted for health status.
Our study did not examine the reasons for why there are observed differences in expectations. However, if these findings can be replicated, there may be many potential reasons to account for the differences in expectations by race. Some possible reasons for the difference in expectations by African American and white patients include patient factors such as knowledge of, beliefs (including cultural beliefs) about and experience with symptoms and health conditions. For example, patients who are more knowledgeable or more experienced with a condition may expect fewer history and exam components to be performed by physicians than those patients who are experiencing a symptom for the first time. System differences such as interaction with specialists would diminish the expectations that a referral to a specialist is necessary or that certain components of the history, physical or data gathering are necessary for the primary care doctor to perform if the specialist has already performed these. Another system variable is the duration of the primary care physician–patient relationship. Long-term relationships with a physician may cause fewer expectations to form at the visit if some items were addressed in previous visits. Furthermore, the documented differential treatment of African Americans and other minorities by the medical profession38 may cause them to have higher expectations for their physicians to do more because they assume that this is what white patients receive. That is, African Americans may develop and express higher expectations as a way to protect themselves against past and potential discrimination. Benkert et al.39 have proposed that perceived racism influences cultural mistrust, including provider mistrust, and it may be that higher expectations are a way to cope with perceived racism. A final potential explanation for the findings that African Americans have more expectations than white patients may be the instrument used to measure expectations. One previous study showed that in non-whites, closed-ended instruments similar to the one used in this study elicited more expectations.17
In an increasingly a consumer-driven health care system, physicians must effectively manage the expectations of all their patients. Previous research has shown that simply being aware of their patient expectations, as when physicians are shown the expectations of their patients elicited by patient questionnaires, does not increase physician fulfilment of the patient's expectations.40 Physicians are more responsive to patient expectations when they are expressed.2 Several interview techniques for eliciting patient expectations have been previously published such as clarifying patient expectations at the beginning of the encounter by asking the patient how they hope the clinician might be able to help them, asking ‘Was there anything else you thought might be helpful or needed?’ at the end of the encounter and eliciting unspoken requests by probing for frequent symptom-specific expectations such as, in patients with a headache, ‘Some patients wonder whether an CT scan or MRI is needed. Had you hoped to have a certain test done?’41 Previous literature suggests that physicians may need to address unmet expectations, for example, by explaining why a test was not ordered or a specialist referral is not needed because unmet expectations may lead to lower patient satisfaction, lower intention to adhere to treatment and more post-visit health system contacts.14 Although elicitation of expectations may lead physicians to think they will be vulnerable to unreasonable patient demands or to longer visit times, a study showed that when physicians were provided with their patient expectations, physicians found encounters less difficult and they did not perceive it increased visit length.42 Ultimately, to improve communication between racial and ethnic minorities, it requires physicians to also build partnerships and establish mutual respect with their patients.43 And to improve the overall health of minorities, Beach et al.44 found that tracking interventions and reminders systems consistently improved the health care quality for racial and ethnic minorities.
This study had several limitations. We did not have the reason(s) for visit. Previous research has also shown that differences in expectations are related to symptoms and/or type of visit.10,15,45 If the reasons for visits vary by race, then this would represent a significant limitation of our study. However, the National Ambulatory Medical Care Survey which reports the reasons for visits by non-Hispanic whites and African Americans in US citizens yearly found that in the randomly sampled 31 269 visits by whites and 7162 visits made by African Americans in 2004, the reason for visit did not vary by race.46 In addition, patients self-administered all the instruments except for the REALM. All instruments had a readability of less than the eighth grade except for the Charlson Comorbidity Index. There is almost no missing data in any literacy group; however, it is still possible that patients with inadequate literacy misinterpreted some of the items. The generalizability of our findings is also limited due to this being a single city sample of patients seeking care at practices based in the Philadelphia VA Hospital and at the UPHS. Finally, we did not have the opportunity to look at the impact of expectations on health-seeking behaviours or outcomes. For example, we do not know whether having greater expectations led to more met or unmet expectations.
Despite these limitations, this study also has several strengths. Our sample was large, spanned several clinic sites and included a large proportion of African Americans, and, unlike many other studies of expectations1,5,45,5,17 adjusted for important confounders including demographics variables, education and health status.15 In addition, we adjusted for health literacy. An increasing body of literature has shown that health literacy is associated with knowledge of a basic medical vocabulary and an understanding of the concept of prevention47 and therefore can effect expectations. Furthermore, this study provides a better understanding of the expectations that different racial subgroups bring to a medical encounter and further supports the practice of patient-centered care.16 If these findings can be replicated, they support that expectations vary significantly by race. Expectations in turn influence patient satisfaction, service utilization and compliance with physician recommendations.5,11,45,17,48 Therefore, these findings underscore the importance that providers should place on detecting and addressing differences in expectations between different racial groups. Future research should attempt to replicate our findings while simultaneously adjusting for the reason for visit. Further research is also needed to understand the impact of the greater expectations held by African-American patients of their physicians.
|
Declaration |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionDeclarationReferences |
|---|
Ethical approval: This study was approved by the Institutional Review Board at the University of Pennsylvania.
Funding: The Veterans Affairs Health Services Research (PCC-98-071-1) to D.A.A. and J.A.S.; the National Cancer Institute (K01 CA-097925) to C.E.G. and the Amos Medical Faculty Development Program of the Robert Wood Johnson Foundation (051895) to C.E.G.
Conflicts of interest: None.
|
Notes |
|---|
Guerra CE, McDonald VJ, Ravenell KL, Asch DA and Shea JA. Effect of race on patient expectations regarding their primary care physicians. Family Practice 2008; 25: 49–55.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionDeclarationReferences |
|---|
1 Peck BM, Asch DA, Goold SD, et al. Measuring patient expectations: does the instrument affect satisfaction or expectations? Med Care (2001) 39:100–108.[CrossRef][Web of Science][Medline]
2 Schwartz RK, Soumerai SB, Avorn J. Physician motivations for non-scientific drug prescribing. Soc Sci Med (1989) 28:577–582.[CrossRef][Web of Science][Medline]
3 Haggerty J, Tudiver F, Brown JB, Herbert C, Ciampi A, Guibert A. Patients' anxiety and expectations: how they influence family physicians' decisions to order cancer screening tests. Can Fam Physician (2005) 51:1658–1659.
4 Joos SK, Hickam DH, Borders LM. Patients' desires and satisfaction in general medicine clinics. Public Health Rep (1993) 108:751–759.[Web of Science][Medline]
5 Kravitz RL, Cope DW, Bhrany V, Leake B. Internal medicine patients’ expectations for care during office visits. J Gen Intern Med (1994) 9:75–81.[Web of Science][Medline]
6 Like R, Zyzanski S. Patient satisfaction with the clinical encounter: social psychological determinants. Soc Sci Med (1987) 24:351–357.[CrossRef][Web of Science][Medline]
7 Ulhmann RF, Inui TS, Pecoraro RE, et al. Relationship of patient request fulfillment to compliance, glycemic control and other health care outcomes in insulin-dependent diabetes. J Gen Intern Med (1988) 3:458–463.[Web of Science][Medline]
8 Brody DS, Miller SM, Lerman CE, et al. The relationship between patients' satisfaction with their physicians and perceptions about interventions they desired and receive. Med Care (1989) 27:1027–1035.[CrossRef][Web of Science][Medline]
9 Eisenthal S, Emery R, Lazare A, et al. "Adherence" and the negotiated approach to patienthood. Arch Gen Pyschiatry (1979) 36:393–398.
10 Rao JK, Weinberger M, Kroenke K. Visit-specific expectations and patient-centered outcomes: a literature review. Arch Fam Med (2000) 1148–1155.
11 Williams S, Weinman J, Dale J, Newman S. Patient expectations: what do primary care patients want from the GP and how far does meeting expectations affect patient satisfaction. Fam Pract (1995) 12:193–201.
12 Shelbourne CD, Hays RD, Ordway L, DiMatteo MR, Kravitz RL. Antecedents of adherence to medical recommendations: results from the Medical Outcomes Study. J Behav Med (1992) 15:447–468.[CrossRef][Web of Science][Medline]
13 O'Brien MK, Petrie K, Raeburn J. Adherence to medication regimens: updating a complex medical issue. Med Care Rev (1992) 49:435–545.[Medline]
14 Bell RA, Kravitz RL, Thom D, Krupat E, Azari R. Unmet expectations for care and the patient-physician relationship. J Gen Intern Med (2002) 817–824.
15 Kravitz RL, Callahan EJ, Paterniti D, Antonius D, Dunham M, Lewis CE. Prevalence and sources of patients’ unmet expectations for care. (1996) 730–737.
16 Institute of Medicine. Crossing the Quality Chasm: A New Health System for the 21st Century (2001) Washington, DC: Institute of Medicine.
17 Kravitz RL, Callahan EJ, Azari R, Antonius D, Lewis CE. Assessing patients’ expectations in ambulatory medical practice. Does the measurement approach make a difference? J Gen Intern Med (1997) 67–72.
18 Ogden J, Jain A. Patients’ experiences and expectations of general practice: a questionnaire study of differences by ethnic group. Br J Gen Pract (2005) 55:351–356.[Medline]
19 Fiscella K, Goodwin MA, Stange KC. Does patient educational level affect office visits to family physicians? J Natl Med Assoc (2002) 94:157–165.[Medline]
20 Parker RM, Davis TC, Williams MV. Patients with Limited Health Literacy (1999) New York: Springer.
21 Shea JA, Aguirre AC, Sabatini J, Weiner J, Schaffer MA, Asch DA. Developing an illustrated version of the Consumer Assessment of Health Plans (CAHPS). Jt Comm J Qual Patient Saf (2005) 1:32–42.
22 de Groot VBH, Lankhorst GJ, Bouter LM. How to measure comorbidity: a critical review of available methods. J Clin Epidemiol (2003) 56:221–229.[CrossRef][Web of Science][Medline]
23 Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis (1987) 40:373–383.[CrossRef][Web of Science][Medline]
24 Charleson ME, SF, McKenzie CR, Fields SD, Braham RL, Douglas RG. Assessing illness severity: does clinical judgment work? J Chron Dis (1986) 39:439–452.[CrossRef][Web of Science][Medline]
25 Inouye SK, PP, Robinson JT, Hughes JS, Horwitz RI, Concato J. Importance of functional measures in predicting mortality among older hospitalized patients. JAMA (1998) 279:1187–1193.
26 Deyo RA, CD, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol (1992) 45:613–619.[CrossRef][Web of Science][Medline]
27 Chin MH, ZJ, Merrell K. Diabetes in the African-American Medicare Population. Morbidity, quality of care and resource utilization. Diabetes Care (1993) 21:1090–1095.[CrossRef]
28 Kiefe CI, FE, Fouad MN, May DS. Chronic disease as a barrier to breast and cervical cancer screening. J Gen Intern Med (1998) 13:357–365.[CrossRef][Web of Science][Medline]
29 Ang DC, Ibrahim SA, Burant CJ, Kwoh CK. Is there a difference in the perception of symptoms between African Americans and whites with osteoarthritis? J Rheumatol (2003) 30:1305–1310.
30 Perkins AJ, Kroenke K, Unutzer J, et al. Common comorbidity scales were similar in their ability to predict health care costs and mortality. J Clin Epidemiol (2004) 57:1040–1048.[CrossRef][Web of Science][Medline]
31 Davis TC, Long SW, Jackson RH, et al. Rapid estimate of adult literacy in medicine: a shortened screening instrument. Fam Pract (1993) 25:391–395.
32 Baker DW, Williams MV, Parker RM, Gazmararian JA, Nurss J. Development of a brief test to measure functional health literacy. Patient Educ Couns (1999) 38:33–42.[CrossRef][Web of Science][Medline]
33 Shea JA, Beers BB, McDonald VJ, Quistberg DA, Ravenell KL, Asch DA. Assessing health literacy in African American and Caucasian adults: disparities in Rapid Estimate of Adult Literacy in Medicine (REALM) scores. Fam Med (2004) 36:575–581.[Web of Science][Medline]
34 Ware JE KM, Keller SD. A 12-item short-form health survey. Med Care (1996) 34:220–233.[CrossRef][Web of Science][Medline]
35 Ware JE Jr, KM, Keller SD. SF-12: How to Score the SF-12 Physical and Mental Health Summary Scales. (1995) Boston, MA: The Health Institute, New England Medical Center.
36 Ware J KM, Keller SD. A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care (1996) 34:220–233.[CrossRef][Web of Science][Medline]
37 Statistical Analysis System (1994) Cary, NC: SAS Institute, Inc.
38 Smedley BD, Stith AY, Nelson AR. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care (2003) Washington, DC.
39 Benkert R, Peters RM, Clark R, Keves-Foster K. Effects of perceived racism, cultural mistrust and trust in providers on satisfaction with care. J Natl Med Assoc (2006) 98:1532–1540.[Medline]
40 Sanchez-Menegay C, Stalder H. Do physicians take into account patients’ expectations? J Gen Intern Med (1994) 9:404–406.[Web of Science][Medline]
41 Kroenke K. Patient expectations for care: how hidden is the agenda? Mayo Clin Proc (1998) 73:191–193.[Web of Science][Medline]
42 Jackson JL, Chamberlin J, Kroenke K. Effects of physician awareness of symptom-related expectations and mental disorders. A controlled trial. Arch Fam Med (1999) 8:135–142.
43 Cooper LA, Beach MC, Johnson RL, Inui TS. Delving below the surface. Understanding how race and ethnicity influence relationships in health care. J Gen Int Med (2006) 21:S21–S27.[Medline]
44 Beach MC, Gary TL, Price EG, et al. Improving health care quality for racial/ethnic minorities: a systematic review of the best evidence regarding provider and organization interventions. BMC Public Health (2006) 6:104–114.[CrossRef][Medline]
45 Marple R, Kroenke K, Lucey C, Wilder J, Lucas C. Concerns and expectations in patients presenting with physical complaints. Frequency, physician perceptions and actions, and 2-week outcome. Arch Intern Med (1997) 157:1482–1488.
46 Hing E, Cherry DK, Woodwell DA. National Ambulatory Medical Care Survey: 2004 Summary. Hyattsville, MD. http://www.cdc.gov/nchs/data/ad/ad374.pdf (accessed on December 12, 2007).
47 Davis T, Dolan N, Ferreira M, et al. The role of inadequate health literacy skills in colorectal cancer screening. Cancer Invest (2001) 19:193–200.[CrossRef][Web of Science][Medline]
48 Barry CA, Bradley CP, Britten N, Stevenson FA, Barber N. Patients’ unvoiced agendas in general practice consultations: qualitative study. BMJ (2000) 320:1246–1250.
CiteULike 
Connotea 
Del.icio.us What's this?
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||