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Influence of English proficiency on patient-provider communication and shared decision-making
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Influence of english proficiency on patient-provider communication and shared decision-making ✩ Anghela Z. Paredesa, Jay J. Idreesa, Eliza W. Beala, Qinyu Chena, Emily Ceriera, Victor Okunrintemib, Griffin Olsena, Steven Suna, Jordan M. Cloyda, Timothy M. Pawlika,∗ a b
Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA Center for Healthcare Advancement and Outcomes, Miami Cardiac and Vascular Institute, Baptist Health South Florida, Miami, FL, USA
a r t i c l e
i n f o
Article history: Received 29 November 2017 Revised 31 December 2017 Accepted 4 January 2018 Available online xxx
a b s t r a c t Background: The number of patients in the United States (US) who speak a language other than English is increasing. We evaluated the impact of English proficiency on self-reported patient-provider communication and shared decision-making. Methods: The 2013–2014 Medical Expenditure Panel Survey database was utilized to identify respondents who spoke a language other than English. Patient–provider communication (PPC) and shared decisionmaking (SDM) scores from 4-12 were categorized as “poor” (4–7), “average” (8–11), and “optimal.” The relationship between PPC, SDM, and English proficiency was analyzed. Results: Among 13,880 respondents, most were white (n = 10,281, 75%), age 18–39 (n = 6,677, 48%), male (n = 7,275, 52%), middle income (n = 4,125, 30%), and born outside of the US (n = 9,125, 65%). English proficiency was rated as “very well” (n = 7,221, 52%), “well” (n = 2,378, 17%), “not well” (n = 2,820, 20%), or “not at all” (n = 1,463, 10%). On multivariable analysis, patients who rated their English as “well” (OR 1.73, 95% CI 1.37–2.18) or “not well” (OR 1.53, 95% CI 1.10–2.14) were more likely to report “poor” PPC (both P < .01). Similarly, SDM was more commonly self-reported as “poor” among patients who reported English proficiency as “not well” (OR 1.31, 95% CI 1.04–1.65, P = .02). Conclusion: Decreased English proficiency was associated with worse self-reported patient–provider communication and shared decision-making. Attention to patients’ language needs is critical to patient satisfaction and improved perception of care. © 2018 Elsevier Inc. All rights reserved.
During the past 50 years, the percentage of persons of Hispanic and Asian ethnicity has more than doubled, and the diversity of the United States is expected to continue to increase, with no racial or ethnic group constituting a majority in the United States by 2065.1 This diversity is reflected in the overwhelming number of individuals who are nonprimary English language speakers. For example, in 2015, it was estimated that >64.7 million persons living in the United States spoke a language other than English at home. Of these, 25.8 million people, including nearly 5 million whom were born in the United States, were of limited English proficiency (LEP).2,3 ✩ Presented at the 13th Annual Academic Surgical Congress, Jacksonville, FL, January 2018. ∗ Corresponding author. Department of Surgery, The Urban Meyer III and Shelley Meyer Chair for Cancer Research, Oncology, Health Services Management and Policy, The Ohio State University, Wexner Medical Center, 395 W. 12th Ave., Suite 670, Columbus, OH 43210, USA. E-mail address: [email protected] (T.M. Pawlik).
Previous research has suggested that health care outcomes and resource utilization are adversely affected by LEP. For example, LEP has been associated with increased unplanned visits to the emergency department (ED), increased frequency of serious adverse events during hospitalization, and greater risk of 30-day readmission after hospitalization.4–6 Patients with LEP are also less likely to understand discharge instructions after an ED visit.4,7 Furthermore, patients who speak a language other than English, especially individuals with LEP, receive lower quality health care and may have worse perceptions of care than English-proficient patients.8–12 The mechanisms behind the association between LEP and worse health care outcomes have not been well investigated. Such data may be important, however, as patient experience scores are being used to guide incentives, reimbursements, and physician ratings.13 Perhaps more importantly, knowledge of how English proficiency affects patient satisfaction may help tailor target interventions for this subset of patients. To this end, shared decision-making (SDM) and patient–provider communication (PPC) are measures that may
https://doi.org/10.1016/j.surg.2018.01.012 0039-6060/© 2018 Elsevier Inc. All rights reserved.
Please cite this article as: A.Z. Paredes et al., Influence of english proficiency on patient-provider communication and shared decisionmaking, Surgery (2018), https://doi.org/10.1016/j.surg.2018.01.012
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be associated with patient satisfaction.14 In turn, LEP may influence the quality of PPC and/or the effectiveness of SDM. PPC is a complex but important part of clinical practice, such that effective PPC has been associated with improved medication adherence, behavior modification, and the decision to undergo recommended surgery.15–19 Similarly, SDM, the concept of informed patients making decisions about their own care in conjunction with their healthcare providers has been associated with improved medication adherence as well as enhanced physical and psychologic wellbeing.20–24 Given that the effect of English proficiency on health care outcomes has been poorly studied, we sought to define the impact of English proficiency on self-reported patient PPC and SDM. Specifically, the objective of the current study was to characterize the range of self-reported PPC and SDM among patients those who speak a language other than English and, specifically, to define the impact of English proficiency on self-reported PPC and SDM. Methods Data source and patient characteristics Sponsored by the Agency for Healthcare Research and Quality, the Medical Expenditure Panel Survey (MEPS) database consists of retrospectively collected data from noninstitutionalized individuals and families from a representative subsample of households that participated in National Health Interview Survey the previous year. Data are collected longitudinally through a panel survey design over a 2-year period through 5 rounds of interviews.25 The survey is composed of 4 components: household, insurance/employer, medical provider, and survey questionnaires. As part of the household survey component questionnaire, respondents were asked questions regarding their usual source of care provider, which could include any of the following: general/family practice, internal medicine, pediatrics, obstetrics/gynecology, surgery, nurse practitioner, physician’s assistant, chiropractor, psychiatrist, or another field. The panel design of the survey over a 2-year period allows researchers to examine how changes in respondents’ health status, income, employment, eligibility for public and private insurance coverage, use of services, and payment for care are related. Languages spoken at home and language proficiency were collected at 4 of the 5 interviews to ensure any new family members were included in the database. For the purposes of this study, the MEPS database was queried from 2013–2014. Individuals who self-identified as speaking a language other than English and self-rated their English proficiency as either “very well,” “well,” “not well,” or “not at all,” were included in the analysis. Only complete responses of individuals aged ≥18 years were analyzed. Data extracted from the data source included patient demographics, health conditions, health status, socio-economic status, and use of medical services, costs, access to care, patient satisfaction, insurance coverage,and social wellness. As MEPS is a publicly available deidentified database, the study was deemed exempt by the institutional review board at Ohio State University. Outcomes The primary outcome of this study was the impact of English proficiency on patient-reported PPC and SDM scores. The PPC score was calculated as a composite score based on responses to the following questions: 1) How often do healthcare providers explain things in a way that was easy to understand? 2) How often do providers show respect for what you had to say? 3) How often do providers spend enough time with you? 4) How often do providers listen carefully to you? Similarly, the SDM score was determined
as a composite score based on responses to the following survey questions: 1) Does your provider ask/show respect for medical, traditional, and alternative treatments that the person is happy with? 2) Does your provider ask you to help make decisions between choices of treatments? 3) Does your provider present and explain all options to you? 4) Does your provider ask about prescription medications/treatments other doctors may give you? All responses were based on a 3-point Likert scale (1 = never/sometimes, 2 = usually, 3 = always); however, responses to questions 3 and 4 of SDM were dichotomized with a response of “yes” being assigned 3 points and “no” assigned 1 point. The numeric total scores for both PPC and SDM were then categorized as poor (4–7), average (8–11), or optimal (12). Secondary outcomes included the impact of English proficiency on the physical health component summary score (PCS) and the mental health component summary score (MCS) based on responses to the Short Form- 12, Version 2. Both PCS and MCS were converted to a binary variable as “high” or “low” with the mean value as the reference. Higher scores imply a better health state in each of those respective components. Additionally, the influence of English proficiency on emergency room visits and inpatient admissions was examined. Emergency room visits and inpatient admissions were converted to a binary variable of ≥1 versus none. Statistical analysis The distribution of patient demographics, socioeconomic status, insurance coverage, and medical conditions across all 4 levels of self-reported English proficiency were compared. Additional analysis was performed by dichotomizing the English proficiency variable into “very well” and LEP, which was defined as patients who reported English proficiency as “well”, “not well”, and “not at all.” Categorical variables are presented as proportions or percentages. Univariable comparisons were performed by using the analysis of variance global test for continuous variables and χ 2 tests for categorical variables. Multivariable logistic regression analysis was performed to evaluate whether LEP was independently associated with PCS, MCS, inpatient stay, or emergency room visit in comparison to those with “very well” English proficiency. Independent variables included in the multivariable analysis were English proficiency, age, insurance coverage, income, region, marital status, place of birth, perceived health status, language spoke at home and during interview, and variables denoting the comorbidities of high blood pressure, coronary heart disease, myocardial infarction, stroke cancer, emphysema, bronchitis, asthma, and cognitive function. For categorical outcome variables with multiple categories, including SDM and PPC, a multivariable ordered logistic regression analysis was performed. All statistical analysis was performed using Stata Statistical Software, release 15 (StataCorp LLC 2017, College Station, TX). Results Among 71,815 participants in the dataset, 13,880 respondents self-identified as speaking a language other than English and self-rated their English proficiency. Most respondents were white (n = 10,281, 75%), aged 18–39 years (n = 6,677, 48%), male (n = 7,275, 52%), middle income (n = 4,125, 30%), born outside of the United States (n = 9,125, 65%), and living in the Western region of the United States (n = 5,812, 42%). English proficiency was rated as “very well” (n = 7,221, 52%), “well” (n = 2,378, 17%), “not well” (n = 2,820, 20%), or “not at all” (n = 1,463, 10%). The majority of respondents who spoke English “very well” were aged 18– 39 years (n = 4,270, 59%), had a middle level income (n = 2,269, 31%), and spoke Spanish at home (n = 4,815, 68%). Patients who self-rated their English proficiency as “not at all” had the highest
Please cite this article as: A.Z. Paredes et al., Influence of english proficiency on patient-provider communication and shared decisionmaking, Surgery (2018), https://doi.org/10.1016/j.surg.2018.01.012
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Table I Sociodemographic characteristics based on level of English proficiency. Very well
Age (n = 13,880) 18–39 40–64 65–74 ≥75 Sex (n = 13,878) Female Male Race/Ethnicity (n = 13,562) White Black Chinese Other Language spoken at home other than English (n = 13,547) Spanish Another language Survey interview language (n = 13,880) English Spanish Spanish and English Other Born in United States (n = 13,875) Yes No Insurance status (n = 13,880) Medicare Medicaid Private Uninsured Other Level of income (n = 13,880) Poor Near poor Low income Middle income High income Region (n = 13,880) Northeast Midwest South West
Well
Not well
Not at all n
P value
n
%
n
%
n
%
%
4,270 2,365 379 207
59.1 32.8 5.2 2.9
1,002 1,128 165 81
42.2 47.5 6.9 3.4
943 1,529 215 133
33.4 54.2 7.6 4.7
462 660 162 179
31.6 45.1 11.1 12.2
3,543 3,678
49.1 50.9
1,187 1,187
50.0 50.0
1,362 1,458
48.3 51.7
511 952
34.9 65.1
5,103 586 363 1,121
71.1 8.2 5.1 15.6
1,610 169 88 443
69.7 7.3 3.8 19.2
2,291 94 27 271
85.4 3.5 1.0 10.1
1,277 39 9 71
91.5 2.8 0.6 5.1
4,815 2,220
68.4 31.6
1,583 742
68.1 31.9
2,266 493
82.1 17.9
1,298 130
90.9 9.1
5,445 1,153 559 64
75.4 16 7.7 1
1,281 833 187 75
54 35 8 3
22 66 6 7
195 1,133 71 64
13 77 5 4
4,211 3,008
58.3 41.7
349 2,024
14.7 85.3
125 2,695
4.4 95.6
65 1,398
4.4 95.6
699 475 1,973 2,192 1,882
9.7 6.6 27.3 30.4 26.1
273 150 460 911 582
11.5 6.3 19.4 38.3 24.5
395 184 370 1,149 722
14.0 6.5 13.1 40.7 25.6
340 109 97 455 462
23.2 7.5 6.6 31.1 31.6
1,214 378 1,185 2,269 2,175
16.8 5.2 16.4 31.4 30.1
539 171 490 769 407
22.7 7.2 20.6 32.4 17.1
802 312 718 776 212
28.4 11.1 25.5 27.5 7.5
567 178 349 311 58
38.8 12.2 23.9 21.3 4.0
1,200 721 2,217 3,050
16.7 10.0 30.8 42.4
417 241 703 1003
17.6 10.2 29.7 42.4
468 260 921 1,155
16.7 9.3 32.8 41.2
194 98 548 604
13.4 6.8 38.0 41.8
<.001
<.001
<.001
<.001
<.001 619 1851 156 194
<.001
<.001
<.001
<.001
distribution of respondents who spoke Spanish at home (n = 1298, 91%), were foreign born (n = 1,398, 91%), and had a poor income level (n = 567, 39%; Table I). Importantly, as English proficiency decreased, the proportion of interviews conducted in English also decreased (“very well” n = 5,445, 75%; “well” n = 1,281, 54 %; “not well” n = 619, 22%; “not at all” n = 195, 13%). Overall, 5,698 (41%) and 6,989 (50%) respondents completed all survey questions to allow the calculation of PPC and SDM scores, respectively. Across all levels of English language proficiency, most respondents reported optimal PPC (n = 4,069, 71%) and SDM (n = 5,896, 84%; Fig 1, A and B). As English proficiency decreased from “very well” to “well” to “not well,” the proportion of respondents with “optimal” SDM and PPC scores decreased (P < .01
for both; Table II). In contrast, the percentage of respondents with “not at all” English proficiency reporting “optimal” PPC and SDM scores was intermediate (Table II). Table III demonstrates the influence of English language proficiency on PPC, SDM, and other health care outcomes using multivariable regression analysis. Patients who self-reported their English proficiency as “well” (OR 1.73, 95% CI 1.37–2.18, P ≤ .01) or “not well” (OR 1.53, 95% CI, 1.10–2.14, P = .01) were more likely to report poor PPC than patients who reported their English proficiency as “very well.” Similarly, SDM was more commonly selfreported as “poor” among patients who reported their English proficiency as “not well” (OR 1.31, 95% CI, 1.04–1.65, P = .02). In contrast, “not at all” English proficiency was not associated with worse
Table II Distribution of SDM and PPC by English proficiency. Very well
SDM (n = 6,989) Optimal Average Poor PPC (n = 5,698) Optimal Average Poor
Well
Not well
Not at all
P value
n
%
n
%
n
%
n
%
3,286 463 87
85.7 12.1 2.3
973 166 23
83.7 14.3 2.0
1,034 187 48
81.5 14.7 3.8
603 102 17
83.5 14.1 2.4
2,333 598 156
75.6 19.4 5.1
602 238 67
66.4 26.2 7.4
700 311 84
63.9 28.4 7.7
434 138 37
71.3 22.7 6.1
.003
<.001
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Table III Multivariate analysis of physical and mental health component summary score, emergency room visit, inpatient admission, shared decision making, and patient provider communication by language proficiency in comparison to those who speak English “very well”. Well
Shared decision making (poor) Patient provider communication (poor) Physical component summary score Mental health component summary score At least 1 emergency room visit in 2013–2014 At least 1 inpatient admission in 2013–2014 Perception of health (poor) ∗
Not well
OR∗
95% CI
P value
OR
∗
1.05 1.73 0.84 0.82 0.84 1.04 1.43
0.84–1.32 1.37–2.18 0.70–1.00 0.69–0.95 0.69–1.03 0.79–1.37 1.28–1.59
.65 .00 .05 .01 .09 .73 .00
1.31 1.53 1.03 0.83 0.78 0.79 1.97
Not at all ∗
95% CI
P value
OR
1.04–1.65 1.10–2.14 0.86–1.24 0.71–0.97 0.64–0.95 0.59–1.04 1.77–2.19
.02 .01 .73 .02 .02 .10 .00
0.96 1.27 1.02 0.86 0.62 0.87 2.6
95% CI
P value
0.72–1.28 0.71–2.26 0.82–1.27 0.72–1.04 0.49–0.80 0.64–1.21 2.30–3.02
.78 .42 .83 .12 .00 .42 .00
Controlling for age, sex, insurance, income, region, marital status, place of birth, and health conditions.
PPC (OR 1.27, 95% CI, 0.71–2.26, P = .42) or SDM (OR 0.96, 95% CI, 0.72–1.28, P = .78). Additionally, English language proficiency affected other health care outcomes (Table III). For example, respondents who self-rated their English proficiency as “not well” and “not at all” were less likely to have one or more visits to the ED, while patients who speak English “well” and “not well” were less likely to have a high mental health score. Interestingly, even after controlling for confounding factors including comorbid health conditions, the odds of poor perceived health increased in a step-wise fashion as English
proficiency decreased (“well” OR 1.43, 95% CI, 1.28–1.59; “not well” OR 1.97, 95% CI, 1.77–2.19; “not at all” OR 2.60, 95% CI, 2.30–3.02). The impact of English proficiency was further evaluated by categorizing English language proficiency as a binary variable (“very well” versus “LEP”; Table IV). On multivariable regression analysis, LEP was independently associated with poor PPC (OR 1.35, 95% CI, 1.16–1.58, P < .01) but not poor SDM (OR 1.13, 95% CI, 0.94– 1.36, P = .20). In addition, LEP was associated with a worse mental health component summary score (OR 0.83, 95% CI, 0.73–0.94, P = .01) and a lower likelihood of a history of ≥1 emergency room visits (OR 0.78, 95% CI, 0.66–0.91, P < .01). Patients with LEP also had a much higher frequency of poor perceived health and decreased perception of “excellent” health (P < .01). Discussion The relative proportion of the US population that is US born and speaks a language other than English has steadily increased during the past 10–30 years.26–28 The fact that many patients are immigrants and US natives who speak a language other than English can have important implications for the health care system. While previous data have suggested that English proficiency may affect health care utilization, data on the effect of language proficiency on self-reported patient outcomes such as PPC and SDM have not been well studied. The present study was important because we used data from the MEPS national dataset to examine the impact of English proficiency on PPC and SDM. Of note, decreased English proficiency was associated with worse self-reported PPC and SDM. In particular, on multivariable analysis, patients who self-reported their English proficiency as “not well” were more likely to report “poor” PPC and “poor” SDM versus patients who reported their English proficiency as “very well.” Of note, when English proficiency was evaluated as a binary variable (e.g. “very well” versus “well”/“not well”/“not at all”) the association remained significant for PPC, but was no longer apparent for SDM. Collectively, the data strongly suggest that language proficiency was an important con-
Table IV Multivariate analysis of physical and mental health component summary score, emergency room visit, inpatient admission, shared decision making, and patient– provider communication comparing limited English proficiency to those who with “very well” English proficiency.
Fig. (A) Proportion of levels of English proficiency stratified by patient–provider communication score. (B) Proportion of levels of English proficiency stratified by shared decision-making communication score.
Shared decision making (poor) Patient Provider communication (poor) Physical component summary score Mental health component summary score At least 1 emergency room visit in 2013–2014 At least 1 inpatient admission in 2013–2014 Perception of health (poor)
OR∗
95% CI
P value
1.13 1.35 0.95 0.83 0.78 0.92 1.79
0.94–1.36 1.16–1.58 0.82–1.10 0.73–0.94 0.66–0.91 0.74–1.15 1.64–1.96
.20 .00 .49 .01 .00 .46 .00
∗ Controlling for age, sex, insurance, income, region, marital status, perception of health, and health conditions.
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tributing factor to how patients perceived and self-reported patient satisfaction metrics. Language proficiency has been evaluated previously relative to patient satisfaction. For example, Barton et al examined shared decision-making in 2 longitudinal, observational cohorts of patients with rheumatoid arthritis.29 In this study, the authors utilized the Interpersonal Processes of Care survey and reported that limited English proficiency was associated with SDM.29 Interestingly, Barton et al also noted that both health literacy and trust in the physician were associated with patient perception of SDM.29 In the present study, using a more nationally representative cohort of patients with a wide range of diagnoses, we similarly noted that decreased English proficiency was associated with worse selfreported PPC and SDM. Of note, federal law has formally recognized the importance of language proficiency. Specifically, Title VI of the 1964 Civil Rights Act mandates that federally funded establishments provide equal treatment regardless of level of English proficiency.30 To this end, a variety of interventions to improve the care of non-native English speakers have been proposed. Jacobs et al reported that the use of professional interpreter services enhanced the delivery of care, specifically flu immunizations, rectal examinationss, and fecal occult blood testing among patients with limited English proficiency.31 Other studies, however, have reported more variable effects of integrating translators on outcomes.31–35 For example, Lee et al noted that Spanish-speaking patients who were seen by a language concordant provider or who had been seen with an interpreter were equally satisfied.35 Interestingly, patients seen using ad hoc or family member interpreters were much less satisfied.35 Data from the present study demonstrated worse PPC and SDM among patients with poor English proficiency. As such, providers should strongly consider more liberal use of interpreters. In fact, data have demonstrated that use of interpreters increases the level of satisfaction of care provided by physicians and improves the quality of patient–physician communication.36,37 Other options, such as decision aids, may also be considered as means to enhance PCC and SDM among patients with limited English proficiency. In one study, a 14-minute Spanish-language video was demonstrated to increase knowledge about colorectal cancer and improved colorectal cancer screening.38 The effect of English proficiency on health care resource utilization has also been a topic of much interest.39–42 Carrasquillo et al examined a cohort of patients who presented to the emergency department of urban teaching hospitals and reported that non-English speakers were less satisfied with their care, less likely to return to the same ED for an emergency, and more likely to report overall problems with care.43 In the present study, patients with decreased English proficiency were also less likely to present to the emergency department compared with patients who had high English proficiency. Such data may indicate that nonEnglish-speaking patients delay presenting for care, which may affect subsequent outcomes. Other authors have noted that nonEnglish speakers have delayed presentation to the emergency room for such conditions as acute appendicitis or acute decompensated heart failure.44,45 While the reasons for the lower emergency room use are undoubtedly multifactorial, further work is needed to examine the potential impact of limited English proficiency, poor PPC and SDM, and health care utilization. The present study had several limitations, including several inherent to the MEPS database. For example, the survey did not directly ask patients whether an interpreter was used during the medical interview. Rather, only the language of the interview was known and not whether interpreters were used. Thus, the data may be skewed in that patients with reduced English proficiency may have been more likely to opt out of the survey or provide incomplete responses due to poor comprehension. As the answers
to the survey questions were self-reported, patients and providers may also have interpreted differently the various levels of English proficiency. In conclusion, patient level of English proficiency was associated with perception of PPC and SDM. Specifically, decreased English proficiency was associated with worse self-reported PPC and SDM. These data also have important implications for providers, as the MEPS data are utilized to inform physician “ratings.” In addition, a better understanding of how limited English proficiency affects health outcomes and patient perceptions can help target strategies to improve patient–provider interaction and overall patient satisfaction. Attention to patient language needs is critical to patient satisfaction and to improved perception of care delivered. Future studies will need to focus on interventions designed to personalize the approach to non-English-proficient patient populations, including increased use of interpreters, decision aids, and cultural sensitivity training for providers. References 1 Pew Research Center. Modern immigration wave brings 59 millions to US, driving population growth and change through 2065: views of immigration’s impact on US society mixed. Washington, DC; 2015. http://www.pewhispanic.org/2015/09/ 28/modern- immigration- wave- brings- 59- million- to- u- s- driving- populationgrowth- and- change- through- 2065/ [Accessed November 18, 2017]. 2 U.S. Census Bureau. 2015 American community survey 1-year estimates: language spoke at home. 2015. https://factfinder.census.gov/bkmk/table/1.0/en/ACS/ 15_1YR/S1601 [Accessed November 16, 2017]. 3 U.S. Census Bureau. 2011–2015 American community survey 5-year estimates: nativity by language spoken at home by ability to speak English for the population 5 years and over. 2015. https://factfinder.census.gov/bkmk/table/1.0/en/ACS/ 15_5YR/B16005. [Accessed November 17, 2017]. 4 Kim EJ, Kim T, Paasche-Orlow MK, Rose AJ, Hanchate AD. Disparities in hypertension associated with limited english proficiency. J Gen Intern Med. 2017;32:632–639. 5 Ngai KM, Grudzen CR, Lee R, Tong VY, Richardson LD, Fernandez A. The association between limited English proficiency and unplanned emergency department revisit within 72 hours. Ann Emerg Med. 2016;68:213–221. 6 Divi C, Koss RG, Schmaltz SP, Loeb JM. Language proficiency and adverse events in US hospitals: a pilot study. Int J Qual Health Care. 2007;19:60–67. 7 Sarver J, Baker DW. Effect of language barriers on follow-up appointments after an emergency department visit. J Gen Intern Med. 20 0 0;15:256–264. 8 Weech-Maldonado R, Morales LS, Spritzer K, Elliott M, Hays RD. Racial and ethnic differences in parents’ assessments of pediatric care in Medicaid managed care. Health Serv Res. 2001;36:575–594. 9 Weech-Maldonado R, Morales LS, Elliott M, Spritzer K, Marshall G, Hays RD. Race/ethnicity, language, and patients’ assessments of care in Medicaid managed care. Health Serv Res. 2003;38:789–808. 10 Weech-Maldonado R, Fongwa MN, Gutierrez P, Hays RD. Language and regional differences in evaluations of Medicare managed care by Hispanics. Health Serv Res. 2008;43:552–568. 11 Wilson CC. Patient safety and healthcare quality: the case for language access. Int J Health Policy Manag. 2013;1:251–253. 12 Eneriz-Wiemer M, Sanders LM, Barr DA, Mendoza FS. Parental limited English proficiency and health outcomes for children with special health care needs: a systematic review. Acad Pediatr. 2014;14:128–136. 13 Mehta SJ. Patient satisfaction reporting and its implications for patient care. AMA J Ethics. 2015;17:616–621. 14 Bartlett G, Blais R, Tamblyn R, Clermont RJ, MacGibbon B. Impact of patient communication problems on the risk of preventable adverse events in acute care settings. CMAJ. 2008;178:1555–1562. 15 Song L, Weaver MA, Chen RC, et al. Associations between patient-provider communication and socio-cultural factors in prostate cancer patients: a cross-sectional evaluation of racial differences. Patient Educ Couns. 2014;97:339–346. 16 Cykert S, Dilworth-Anderson P, Monroe MH, et al. Factors associated with decisions to undergo surgery among patients with newly diagnosed early-stage lung cancer. JAMA. 2010;303:2368–2376. 17 Stewart MA. Effective physician-patient communication and health outcomes: a review. CMAJ. 1995;152:1423–1433. 18 Bull SA, Hu XH, Hunkeler EM, et al. Discontinuation of use and switching of antidepressants: influence of patient-physician communication. JAMA. 2002;288:1403–1409. 19 Ciechanowski PS, Katon WJ, Russo JE, Walker EA. The patient-provider relationship: attachment theory and adherence to treatment in diabetes. Am J Psychiatry. 2001;158:29–35. 20 Kunneman M, Montori VM, Castaneda-Guarderas A, Hess EP. What is shared decision making? (and what it is not). Acad Emerg Med. 2016;23:1320–1324. 21 Durand MA, Barr PJ, Walsh T, Elwyn G. Incentivizing shared decision making in the USA—where are we now? Healthc (Amst). 2015;3:97–101. 22 Oshima Lee E, Emanuel EJ. Shared decision making to improve care and reduce costs. N Engl J Med. 2013;368:6–8.
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23 van Roosmalen MS, Stalmeier PF, Verhoef LC, et al. Randomized trial of a shared decision-making intervention consisting of trade-offs and individualized treatment information for BRCA1/2 mutation carriers. J Clin Oncol. 2004;22:3293–3301. 24 Ludman E, Katon W, Bush T, et al. Behavioural factors associated with symptom outcomes in a primary care-based depression prevention intervention trial. Psychol Med. 2003;33:1061–1070. 25 Agency for Healthcare Research and Quality. MEPS-HC panel design and collection process. http://www.meps.ahrq.gov/mepsweb/survey_comp/hc_data_ collection.jsp. [Accessed November 17, 2017]. 26 Batalova J, Zong J. Language diversity and English proficiency in the United States. 2016. https://www.migrationpolicy.org/article/language-diversity-and-englishproficiency- united- states [Accessed November 28, 2017]. 27 2005 American community survey: place of birth by language spoke at home and ability to speak English in the United States; 2005. https://factfinder.census. gov/bkmk/table/1.0/en/ACS/05_EST/B06007. [Accessed November 28, 2017]. 28 U.S. Census Bureau. 2016 American community survey 1-year estimates: place of birth by language spoke at home and ability to speak English in the United States. 2016. https://factfinder.census.gov/bkmk/table/1.0/en/ACS/16_1YR/ B06007 [Accessed November 28, 2017]. 29 Barton JL, Trupin L, Tonner C, et al. English language proficiency, health literacy, and trust in physician are associated with shared decision making in rheumatoid arthritis. J Rheumatol. 2014;41:1290–1297. 30 Prohibition against exclusion from participation in, denial of benefits of, and discrimination under federally assisted programs on ground of race, color, or national origin. Title IV of the Civil Rights Act of 1964, 42 USCS § 20 0 0d; 1964. https://www.law.cornell.edu/uscode/text/42/20 0 0d. [Accessed November 28, 2017]. 31 Jacobs EA, Lauderdale DS, Meltzer D, Shorey JM, Levinson W, Thisted RA. Impact of interpreter services on delivery of health care to limited-English-proficient patients. J Gen Intern Med. 2001;16:468–474. 32 López L, Rodriguez F, Huerta D, Soukup J, Hicks L. Use of interpreters by physicians for hospitalized limited English proficient patients and its impact on patient outcomes. J Gen Intern Med. 2015;30:783–789. 33 Karliner LS, Jacobs EA, Chen AH, Mutha S. Do professional interpreters improve clinical care for patients with limited English proficiency? A systematic review of the literature. Health Serv Res. 2007;42:727–754.
34 Lee JS, Nápoles A, Mutha S, et al. Hospital discharge preparedness for patients with limited English proficiency: a mixed methods study of bedside interpreter– phones. Patient Educ Couns. 2018;101:25–32. 35 Lee LJ, Batal HA, Maselli JH, Kutner JS. Effect of Spanish interpretation method on patient satisfaction in an urban walk-in clinic. J Gen Intern Med. 2002;17:641–645. 36 Karliner LS, Pérez-Stable EJ, Gildengorin G. The language divide. The importance of training in the use of interpreters for outpatient practice. J Gen Intern Med. 2004;19:175–183. 37 Hornberger J, Itakura H, Wilson SR. Bridging language and cultural barriers between physicians and patients. Public Health Rep. 1997;112:410–417. 38 Reuland DS, Ko LK, Fernandez A, Braswell LC, Pignone M. Testing a Spanish-language colorectal cancer screening decision aid in Latinos with limited English proficiency: results from a pre-post trial and four month follow-up survey. BMC Med Inform Decis Mak. 2012;12:53. 39 Ai AL, Appel HB, Huang B, Lee K. Overall health and healthcare utilization among Latino American women in the United States. J Womens Health (Larchmt). 2012;21:878–885. 40 Valet RS, Gebretsadik T, Carroll KN, et al. Increased healthcare resource utilization for acute respiratory illness among Latino infants. J Pediatr. 2013;163:1186–1191. 41 De Jesus M, Xiao C. Predicting health care utilization among Latinos: health locus of control beliefs or access factors? Health Educ Behav. 2014;41:423–430. 42 Ai AL, Noël LT, Appel HB, Huang B, Hefley WE. Overall health and health care utilization among Latino American men in the United States. Am J Mens Health. 2013;7:6–17. 43 Carrasquillo O, Orav EJ, Brennan TA, Burstin HR. Impact of language barriers on patient satisfaction in an emergency department. J Gen Intern Med. 1999;14:82–87. 44 Darling C, Saczynski JS, McManus DD, Lessard D, Spencer FA, Goldberg RJ. Delayed hospital presentation in acute decompensated heart failure: clinical and patient reported factors. Heart Lung. 2013;42:281–286. 45 Comparative Effectiveness Research Translation Network’s Collaborative for Healthcare Research in Behavioral Economics and Decision Sciences (CERTAIN– CHOICES). Factors influencing delayed hospital presentation in patients with appendicitis: the APPE survey. J Surg Res. 2017;207:123–130.
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Contents lists available at ScienceDirect
Surgery journal homepage: www.elsevier.com/locate/surg
Influence of english proficiency on patient-provider communication and shared decision-making ✩ Anghela Z. Paredesa, Jay J. Idreesa, Eliza W. Beala, Qinyu Chena, Emily Ceriera, Victor Okunrintemib, Griffin Olsena, Steven Suna, Jordan M. Cloyda, Timothy M. Pawlika,∗ a b
Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA Center for Healthcare Advancement and Outcomes, Miami Cardiac and Vascular Institute, Baptist Health South Florida, Miami, FL, USA
a r t i c l e
i n f o
Article history: Received 29 November 2017 Revised 31 December 2017 Accepted 4 January 2018 Available online xxx
a b s t r a c t Background: The number of patients in the United States (US) who speak a language other than English is increasing. We evaluated the impact of English proficiency on self-reported patient-provider communication and shared decision-making. Methods: The 2013–2014 Medical Expenditure Panel Survey database was utilized to identify respondents who spoke a language other than English. Patient–provider communication (PPC) and shared decisionmaking (SDM) scores from 4-12 were categorized as “poor” (4–7), “average” (8–11), and “optimal.” The relationship between PPC, SDM, and English proficiency was analyzed. Results: Among 13,880 respondents, most were white (n = 10,281, 75%), age 18–39 (n = 6,677, 48%), male (n = 7,275, 52%), middle income (n = 4,125, 30%), and born outside of the US (n = 9,125, 65%). English proficiency was rated as “very well” (n = 7,221, 52%), “well” (n = 2,378, 17%), “not well” (n = 2,820, 20%), or “not at all” (n = 1,463, 10%). On multivariable analysis, patients who rated their English as “well” (OR 1.73, 95% CI 1.37–2.18) or “not well” (OR 1.53, 95% CI 1.10–2.14) were more likely to report “poor” PPC (both P < .01). Similarly, SDM was more commonly self-reported as “poor” among patients who reported English proficiency as “not well” (OR 1.31, 95% CI 1.04–1.65, P = .02). Conclusion: Decreased English proficiency was associated with worse self-reported patient–provider communication and shared decision-making. Attention to patients’ language needs is critical to patient satisfaction and improved perception of care. © 2018 Elsevier Inc. All rights reserved.
During the past 50 years, the percentage of persons of Hispanic and Asian ethnicity has more than doubled, and the diversity of the United States is expected to continue to increase, with no racial or ethnic group constituting a majority in the United States by 2065.1 This diversity is reflected in the overwhelming number of individuals who are nonprimary English language speakers. For example, in 2015, it was estimated that >64.7 million persons living in the United States spoke a language other than English at home. Of these, 25.8 million people, including nearly 5 million whom were born in the United States, were of limited English proficiency (LEP).2,3 ✩ Presented at the 13th Annual Academic Surgical Congress, Jacksonville, FL, January 2018. ∗ Corresponding author. Department of Surgery, The Urban Meyer III and Shelley Meyer Chair for Cancer Research, Oncology, Health Services Management and Policy, The Ohio State University, Wexner Medical Center, 395 W. 12th Ave., Suite 670, Columbus, OH 43210, USA. E-mail address: [email protected] (T.M. Pawlik).
Previous research has suggested that health care outcomes and resource utilization are adversely affected by LEP. For example, LEP has been associated with increased unplanned visits to the emergency department (ED), increased frequency of serious adverse events during hospitalization, and greater risk of 30-day readmission after hospitalization.4–6 Patients with LEP are also less likely to understand discharge instructions after an ED visit.4,7 Furthermore, patients who speak a language other than English, especially individuals with LEP, receive lower quality health care and may have worse perceptions of care than English-proficient patients.8–12 The mechanisms behind the association between LEP and worse health care outcomes have not been well investigated. Such data may be important, however, as patient experience scores are being used to guide incentives, reimbursements, and physician ratings.13 Perhaps more importantly, knowledge of how English proficiency affects patient satisfaction may help tailor target interventions for this subset of patients. To this end, shared decision-making (SDM) and patient–provider communication (PPC) are measures that may
https://doi.org/10.1016/j.surg.2018.01.012 0039-6060/© 2018 Elsevier Inc. All rights reserved.
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be associated with patient satisfaction.14 In turn, LEP may influence the quality of PPC and/or the effectiveness of SDM. PPC is a complex but important part of clinical practice, such that effective PPC has been associated with improved medication adherence, behavior modification, and the decision to undergo recommended surgery.15–19 Similarly, SDM, the concept of informed patients making decisions about their own care in conjunction with their healthcare providers has been associated with improved medication adherence as well as enhanced physical and psychologic wellbeing.20–24 Given that the effect of English proficiency on health care outcomes has been poorly studied, we sought to define the impact of English proficiency on self-reported patient PPC and SDM. Specifically, the objective of the current study was to characterize the range of self-reported PPC and SDM among patients those who speak a language other than English and, specifically, to define the impact of English proficiency on self-reported PPC and SDM. Methods Data source and patient characteristics Sponsored by the Agency for Healthcare Research and Quality, the Medical Expenditure Panel Survey (MEPS) database consists of retrospectively collected data from noninstitutionalized individuals and families from a representative subsample of households that participated in National Health Interview Survey the previous year. Data are collected longitudinally through a panel survey design over a 2-year period through 5 rounds of interviews.25 The survey is composed of 4 components: household, insurance/employer, medical provider, and survey questionnaires. As part of the household survey component questionnaire, respondents were asked questions regarding their usual source of care provider, which could include any of the following: general/family practice, internal medicine, pediatrics, obstetrics/gynecology, surgery, nurse practitioner, physician’s assistant, chiropractor, psychiatrist, or another field. The panel design of the survey over a 2-year period allows researchers to examine how changes in respondents’ health status, income, employment, eligibility for public and private insurance coverage, use of services, and payment for care are related. Languages spoken at home and language proficiency were collected at 4 of the 5 interviews to ensure any new family members were included in the database. For the purposes of this study, the MEPS database was queried from 2013–2014. Individuals who self-identified as speaking a language other than English and self-rated their English proficiency as either “very well,” “well,” “not well,” or “not at all,” were included in the analysis. Only complete responses of individuals aged ≥18 years were analyzed. Data extracted from the data source included patient demographics, health conditions, health status, socio-economic status, and use of medical services, costs, access to care, patient satisfaction, insurance coverage,and social wellness. As MEPS is a publicly available deidentified database, the study was deemed exempt by the institutional review board at Ohio State University. Outcomes The primary outcome of this study was the impact of English proficiency on patient-reported PPC and SDM scores. The PPC score was calculated as a composite score based on responses to the following questions: 1) How often do healthcare providers explain things in a way that was easy to understand? 2) How often do providers show respect for what you had to say? 3) How often do providers spend enough time with you? 4) How often do providers listen carefully to you? Similarly, the SDM score was determined
as a composite score based on responses to the following survey questions: 1) Does your provider ask/show respect for medical, traditional, and alternative treatments that the person is happy with? 2) Does your provider ask you to help make decisions between choices of treatments? 3) Does your provider present and explain all options to you? 4) Does your provider ask about prescription medications/treatments other doctors may give you? All responses were based on a 3-point Likert scale (1 = never/sometimes, 2 = usually, 3 = always); however, responses to questions 3 and 4 of SDM were dichotomized with a response of “yes” being assigned 3 points and “no” assigned 1 point. The numeric total scores for both PPC and SDM were then categorized as poor (4–7), average (8–11), or optimal (12). Secondary outcomes included the impact of English proficiency on the physical health component summary score (PCS) and the mental health component summary score (MCS) based on responses to the Short Form- 12, Version 2. Both PCS and MCS were converted to a binary variable as “high” or “low” with the mean value as the reference. Higher scores imply a better health state in each of those respective components. Additionally, the influence of English proficiency on emergency room visits and inpatient admissions was examined. Emergency room visits and inpatient admissions were converted to a binary variable of ≥1 versus none. Statistical analysis The distribution of patient demographics, socioeconomic status, insurance coverage, and medical conditions across all 4 levels of self-reported English proficiency were compared. Additional analysis was performed by dichotomizing the English proficiency variable into “very well” and LEP, which was defined as patients who reported English proficiency as “well”, “not well”, and “not at all.” Categorical variables are presented as proportions or percentages. Univariable comparisons were performed by using the analysis of variance global test for continuous variables and χ 2 tests for categorical variables. Multivariable logistic regression analysis was performed to evaluate whether LEP was independently associated with PCS, MCS, inpatient stay, or emergency room visit in comparison to those with “very well” English proficiency. Independent variables included in the multivariable analysis were English proficiency, age, insurance coverage, income, region, marital status, place of birth, perceived health status, language spoke at home and during interview, and variables denoting the comorbidities of high blood pressure, coronary heart disease, myocardial infarction, stroke cancer, emphysema, bronchitis, asthma, and cognitive function. For categorical outcome variables with multiple categories, including SDM and PPC, a multivariable ordered logistic regression analysis was performed. All statistical analysis was performed using Stata Statistical Software, release 15 (StataCorp LLC 2017, College Station, TX). Results Among 71,815 participants in the dataset, 13,880 respondents self-identified as speaking a language other than English and self-rated their English proficiency. Most respondents were white (n = 10,281, 75%), aged 18–39 years (n = 6,677, 48%), male (n = 7,275, 52%), middle income (n = 4,125, 30%), born outside of the United States (n = 9,125, 65%), and living in the Western region of the United States (n = 5,812, 42%). English proficiency was rated as “very well” (n = 7,221, 52%), “well” (n = 2,378, 17%), “not well” (n = 2,820, 20%), or “not at all” (n = 1,463, 10%). The majority of respondents who spoke English “very well” were aged 18– 39 years (n = 4,270, 59%), had a middle level income (n = 2,269, 31%), and spoke Spanish at home (n = 4,815, 68%). Patients who self-rated their English proficiency as “not at all” had the highest
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Table I Sociodemographic characteristics based on level of English proficiency. Very well
Age (n = 13,880) 18–39 40–64 65–74 ≥75 Sex (n = 13,878) Female Male Race/Ethnicity (n = 13,562) White Black Chinese Other Language spoken at home other than English (n = 13,547) Spanish Another language Survey interview language (n = 13,880) English Spanish Spanish and English Other Born in United States (n = 13,875) Yes No Insurance status (n = 13,880) Medicare Medicaid Private Uninsured Other Level of income (n = 13,880) Poor Near poor Low income Middle income High income Region (n = 13,880) Northeast Midwest South West
Well
Not well
Not at all n
P value
n
%
n
%
n
%
%
4,270 2,365 379 207
59.1 32.8 5.2 2.9
1,002 1,128 165 81
42.2 47.5 6.9 3.4
943 1,529 215 133
33.4 54.2 7.6 4.7
462 660 162 179
31.6 45.1 11.1 12.2
3,543 3,678
49.1 50.9
1,187 1,187
50.0 50.0
1,362 1,458
48.3 51.7
511 952
34.9 65.1
5,103 586 363 1,121
71.1 8.2 5.1 15.6
1,610 169 88 443
69.7 7.3 3.8 19.2
2,291 94 27 271
85.4 3.5 1.0 10.1
1,277 39 9 71
91.5 2.8 0.6 5.1
4,815 2,220
68.4 31.6
1,583 742
68.1 31.9
2,266 493
82.1 17.9
1,298 130
90.9 9.1
5,445 1,153 559 64
75.4 16 7.7 1
1,281 833 187 75
54 35 8 3
22 66 6 7
195 1,133 71 64
13 77 5 4
4,211 3,008
58.3 41.7
349 2,024
14.7 85.3
125 2,695
4.4 95.6
65 1,398
4.4 95.6
699 475 1,973 2,192 1,882
9.7 6.6 27.3 30.4 26.1
273 150 460 911 582
11.5 6.3 19.4 38.3 24.5
395 184 370 1,149 722
14.0 6.5 13.1 40.7 25.6
340 109 97 455 462
23.2 7.5 6.6 31.1 31.6
1,214 378 1,185 2,269 2,175
16.8 5.2 16.4 31.4 30.1
539 171 490 769 407
22.7 7.2 20.6 32.4 17.1
802 312 718 776 212
28.4 11.1 25.5 27.5 7.5
567 178 349 311 58
38.8 12.2 23.9 21.3 4.0
1,200 721 2,217 3,050
16.7 10.0 30.8 42.4
417 241 703 1003
17.6 10.2 29.7 42.4
468 260 921 1,155
16.7 9.3 32.8 41.2
194 98 548 604
13.4 6.8 38.0 41.8
<.001
<.001
<.001
<.001
<.001 619 1851 156 194
<.001
<.001
<.001
<.001
distribution of respondents who spoke Spanish at home (n = 1298, 91%), were foreign born (n = 1,398, 91%), and had a poor income level (n = 567, 39%; Table I). Importantly, as English proficiency decreased, the proportion of interviews conducted in English also decreased (“very well” n = 5,445, 75%; “well” n = 1,281, 54 %; “not well” n = 619, 22%; “not at all” n = 195, 13%). Overall, 5,698 (41%) and 6,989 (50%) respondents completed all survey questions to allow the calculation of PPC and SDM scores, respectively. Across all levels of English language proficiency, most respondents reported optimal PPC (n = 4,069, 71%) and SDM (n = 5,896, 84%; Fig 1, A and B). As English proficiency decreased from “very well” to “well” to “not well,” the proportion of respondents with “optimal” SDM and PPC scores decreased (P < .01
for both; Table II). In contrast, the percentage of respondents with “not at all” English proficiency reporting “optimal” PPC and SDM scores was intermediate (Table II). Table III demonstrates the influence of English language proficiency on PPC, SDM, and other health care outcomes using multivariable regression analysis. Patients who self-reported their English proficiency as “well” (OR 1.73, 95% CI 1.37–2.18, P ≤ .01) or “not well” (OR 1.53, 95% CI, 1.10–2.14, P = .01) were more likely to report poor PPC than patients who reported their English proficiency as “very well.” Similarly, SDM was more commonly selfreported as “poor” among patients who reported their English proficiency as “not well” (OR 1.31, 95% CI, 1.04–1.65, P = .02). In contrast, “not at all” English proficiency was not associated with worse
Table II Distribution of SDM and PPC by English proficiency. Very well
SDM (n = 6,989) Optimal Average Poor PPC (n = 5,698) Optimal Average Poor
Well
Not well
Not at all
P value
n
%
n
%
n
%
n
%
3,286 463 87
85.7 12.1 2.3
973 166 23
83.7 14.3 2.0
1,034 187 48
81.5 14.7 3.8
603 102 17
83.5 14.1 2.4
2,333 598 156
75.6 19.4 5.1
602 238 67
66.4 26.2 7.4
700 311 84
63.9 28.4 7.7
434 138 37
71.3 22.7 6.1
.003
<.001
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Table III Multivariate analysis of physical and mental health component summary score, emergency room visit, inpatient admission, shared decision making, and patient provider communication by language proficiency in comparison to those who speak English “very well”. Well
Shared decision making (poor) Patient provider communication (poor) Physical component summary score Mental health component summary score At least 1 emergency room visit in 2013–2014 At least 1 inpatient admission in 2013–2014 Perception of health (poor) ∗
Not well
OR∗
95% CI
P value
OR
∗
1.05 1.73 0.84 0.82 0.84 1.04 1.43
0.84–1.32 1.37–2.18 0.70–1.00 0.69–0.95 0.69–1.03 0.79–1.37 1.28–1.59
.65 .00 .05 .01 .09 .73 .00
1.31 1.53 1.03 0.83 0.78 0.79 1.97
Not at all ∗
95% CI
P value
OR
1.04–1.65 1.10–2.14 0.86–1.24 0.71–0.97 0.64–0.95 0.59–1.04 1.77–2.19
.02 .01 .73 .02 .02 .10 .00
0.96 1.27 1.02 0.86 0.62 0.87 2.6
95% CI
P value
0.72–1.28 0.71–2.26 0.82–1.27 0.72–1.04 0.49–0.80 0.64–1.21 2.30–3.02
.78 .42 .83 .12 .00 .42 .00
Controlling for age, sex, insurance, income, region, marital status, place of birth, and health conditions.
PPC (OR 1.27, 95% CI, 0.71–2.26, P = .42) or SDM (OR 0.96, 95% CI, 0.72–1.28, P = .78). Additionally, English language proficiency affected other health care outcomes (Table III). For example, respondents who self-rated their English proficiency as “not well” and “not at all” were less likely to have one or more visits to the ED, while patients who speak English “well” and “not well” were less likely to have a high mental health score. Interestingly, even after controlling for confounding factors including comorbid health conditions, the odds of poor perceived health increased in a step-wise fashion as English
proficiency decreased (“well” OR 1.43, 95% CI, 1.28–1.59; “not well” OR 1.97, 95% CI, 1.77–2.19; “not at all” OR 2.60, 95% CI, 2.30–3.02). The impact of English proficiency was further evaluated by categorizing English language proficiency as a binary variable (“very well” versus “LEP”; Table IV). On multivariable regression analysis, LEP was independently associated with poor PPC (OR 1.35, 95% CI, 1.16–1.58, P < .01) but not poor SDM (OR 1.13, 95% CI, 0.94– 1.36, P = .20). In addition, LEP was associated with a worse mental health component summary score (OR 0.83, 95% CI, 0.73–0.94, P = .01) and a lower likelihood of a history of ≥1 emergency room visits (OR 0.78, 95% CI, 0.66–0.91, P < .01). Patients with LEP also had a much higher frequency of poor perceived health and decreased perception of “excellent” health (P < .01). Discussion The relative proportion of the US population that is US born and speaks a language other than English has steadily increased during the past 10–30 years.26–28 The fact that many patients are immigrants and US natives who speak a language other than English can have important implications for the health care system. While previous data have suggested that English proficiency may affect health care utilization, data on the effect of language proficiency on self-reported patient outcomes such as PPC and SDM have not been well studied. The present study was important because we used data from the MEPS national dataset to examine the impact of English proficiency on PPC and SDM. Of note, decreased English proficiency was associated with worse self-reported PPC and SDM. In particular, on multivariable analysis, patients who self-reported their English proficiency as “not well” were more likely to report “poor” PPC and “poor” SDM versus patients who reported their English proficiency as “very well.” Of note, when English proficiency was evaluated as a binary variable (e.g. “very well” versus “well”/“not well”/“not at all”) the association remained significant for PPC, but was no longer apparent for SDM. Collectively, the data strongly suggest that language proficiency was an important con-
Table IV Multivariate analysis of physical and mental health component summary score, emergency room visit, inpatient admission, shared decision making, and patient– provider communication comparing limited English proficiency to those who with “very well” English proficiency.
Fig. (A) Proportion of levels of English proficiency stratified by patient–provider communication score. (B) Proportion of levels of English proficiency stratified by shared decision-making communication score.
Shared decision making (poor) Patient Provider communication (poor) Physical component summary score Mental health component summary score At least 1 emergency room visit in 2013–2014 At least 1 inpatient admission in 2013–2014 Perception of health (poor)
OR∗
95% CI
P value
1.13 1.35 0.95 0.83 0.78 0.92 1.79
0.94–1.36 1.16–1.58 0.82–1.10 0.73–0.94 0.66–0.91 0.74–1.15 1.64–1.96
.20 .00 .49 .01 .00 .46 .00
∗ Controlling for age, sex, insurance, income, region, marital status, perception of health, and health conditions.
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tributing factor to how patients perceived and self-reported patient satisfaction metrics. Language proficiency has been evaluated previously relative to patient satisfaction. For example, Barton et al examined shared decision-making in 2 longitudinal, observational cohorts of patients with rheumatoid arthritis.29 In this study, the authors utilized the Interpersonal Processes of Care survey and reported that limited English proficiency was associated with SDM.29 Interestingly, Barton et al also noted that both health literacy and trust in the physician were associated with patient perception of SDM.29 In the present study, using a more nationally representative cohort of patients with a wide range of diagnoses, we similarly noted that decreased English proficiency was associated with worse selfreported PPC and SDM. Of note, federal law has formally recognized the importance of language proficiency. Specifically, Title VI of the 1964 Civil Rights Act mandates that federally funded establishments provide equal treatment regardless of level of English proficiency.30 To this end, a variety of interventions to improve the care of non-native English speakers have been proposed. Jacobs et al reported that the use of professional interpreter services enhanced the delivery of care, specifically flu immunizations, rectal examinationss, and fecal occult blood testing among patients with limited English proficiency.31 Other studies, however, have reported more variable effects of integrating translators on outcomes.31–35 For example, Lee et al noted that Spanish-speaking patients who were seen by a language concordant provider or who had been seen with an interpreter were equally satisfied.35 Interestingly, patients seen using ad hoc or family member interpreters were much less satisfied.35 Data from the present study demonstrated worse PPC and SDM among patients with poor English proficiency. As such, providers should strongly consider more liberal use of interpreters. In fact, data have demonstrated that use of interpreters increases the level of satisfaction of care provided by physicians and improves the quality of patient–physician communication.36,37 Other options, such as decision aids, may also be considered as means to enhance PCC and SDM among patients with limited English proficiency. In one study, a 14-minute Spanish-language video was demonstrated to increase knowledge about colorectal cancer and improved colorectal cancer screening.38 The effect of English proficiency on health care resource utilization has also been a topic of much interest.39–42 Carrasquillo et al examined a cohort of patients who presented to the emergency department of urban teaching hospitals and reported that non-English speakers were less satisfied with their care, less likely to return to the same ED for an emergency, and more likely to report overall problems with care.43 In the present study, patients with decreased English proficiency were also less likely to present to the emergency department compared with patients who had high English proficiency. Such data may indicate that nonEnglish-speaking patients delay presenting for care, which may affect subsequent outcomes. Other authors have noted that nonEnglish speakers have delayed presentation to the emergency room for such conditions as acute appendicitis or acute decompensated heart failure.44,45 While the reasons for the lower emergency room use are undoubtedly multifactorial, further work is needed to examine the potential impact of limited English proficiency, poor PPC and SDM, and health care utilization. The present study had several limitations, including several inherent to the MEPS database. For example, the survey did not directly ask patients whether an interpreter was used during the medical interview. Rather, only the language of the interview was known and not whether interpreters were used. Thus, the data may be skewed in that patients with reduced English proficiency may have been more likely to opt out of the survey or provide incomplete responses due to poor comprehension. As the answers
to the survey questions were self-reported, patients and providers may also have interpreted differently the various levels of English proficiency. In conclusion, patient level of English proficiency was associated with perception of PPC and SDM. Specifically, decreased English proficiency was associated with worse self-reported PPC and SDM. These data also have important implications for providers, as the MEPS data are utilized to inform physician “ratings.” In addition, a better understanding of how limited English proficiency affects health outcomes and patient perceptions can help target strategies to improve patient–provider interaction and overall patient satisfaction. Attention to patient language needs is critical to patient satisfaction and to improved perception of care delivered. Future studies will need to focus on interventions designed to personalize the approach to non-English-proficient patient populations, including increased use of interpreters, decision aids, and cultural sensitivity training for providers. References 1 Pew Research Center. Modern immigration wave brings 59 millions to US, driving population growth and change through 2065: views of immigration’s impact on US society mixed. Washington, DC; 2015. http://www.pewhispanic.org/2015/09/ 28/modern- immigration- wave- brings- 59- million- to- u- s- driving- populationgrowth- and- change- through- 2065/ [Accessed November 18, 2017]. 2 U.S. Census Bureau. 2015 American community survey 1-year estimates: language spoke at home. 2015. https://factfinder.census.gov/bkmk/table/1.0/en/ACS/ 15_1YR/S1601 [Accessed November 16, 2017]. 3 U.S. Census Bureau. 2011–2015 American community survey 5-year estimates: nativity by language spoken at home by ability to speak English for the population 5 years and over. 2015. https://factfinder.census.gov/bkmk/table/1.0/en/ACS/ 15_5YR/B16005. [Accessed November 17, 2017]. 4 Kim EJ, Kim T, Paasche-Orlow MK, Rose AJ, Hanchate AD. Disparities in hypertension associated with limited english proficiency. J Gen Intern Med. 2017;32:632–639. 5 Ngai KM, Grudzen CR, Lee R, Tong VY, Richardson LD, Fernandez A. The association between limited English proficiency and unplanned emergency department revisit within 72 hours. Ann Emerg Med. 2016;68:213–221. 6 Divi C, Koss RG, Schmaltz SP, Loeb JM. Language proficiency and adverse events in US hospitals: a pilot study. Int J Qual Health Care. 2007;19:60–67. 7 Sarver J, Baker DW. Effect of language barriers on follow-up appointments after an emergency department visit. J Gen Intern Med. 20 0 0;15:256–264. 8 Weech-Maldonado R, Morales LS, Spritzer K, Elliott M, Hays RD. Racial and ethnic differences in parents’ assessments of pediatric care in Medicaid managed care. Health Serv Res. 2001;36:575–594. 9 Weech-Maldonado R, Morales LS, Elliott M, Spritzer K, Marshall G, Hays RD. Race/ethnicity, language, and patients’ assessments of care in Medicaid managed care. Health Serv Res. 2003;38:789–808. 10 Weech-Maldonado R, Fongwa MN, Gutierrez P, Hays RD. Language and regional differences in evaluations of Medicare managed care by Hispanics. Health Serv Res. 2008;43:552–568. 11 Wilson CC. Patient safety and healthcare quality: the case for language access. Int J Health Policy Manag. 2013;1:251–253. 12 Eneriz-Wiemer M, Sanders LM, Barr DA, Mendoza FS. Parental limited English proficiency and health outcomes for children with special health care needs: a systematic review. Acad Pediatr. 2014;14:128–136. 13 Mehta SJ. Patient satisfaction reporting and its implications for patient care. AMA J Ethics. 2015;17:616–621. 14 Bartlett G, Blais R, Tamblyn R, Clermont RJ, MacGibbon B. Impact of patient communication problems on the risk of preventable adverse events in acute care settings. CMAJ. 2008;178:1555–1562. 15 Song L, Weaver MA, Chen RC, et al. Associations between patient-provider communication and socio-cultural factors in prostate cancer patients: a cross-sectional evaluation of racial differences. Patient Educ Couns. 2014;97:339–346. 16 Cykert S, Dilworth-Anderson P, Monroe MH, et al. Factors associated with decisions to undergo surgery among patients with newly diagnosed early-stage lung cancer. JAMA. 2010;303:2368–2376. 17 Stewart MA. Effective physician-patient communication and health outcomes: a review. CMAJ. 1995;152:1423–1433. 18 Bull SA, Hu XH, Hunkeler EM, et al. Discontinuation of use and switching of antidepressants: influence of patient-physician communication. JAMA. 2002;288:1403–1409. 19 Ciechanowski PS, Katon WJ, Russo JE, Walker EA. The patient-provider relationship: attachment theory and adherence to treatment in diabetes. Am J Psychiatry. 2001;158:29–35. 20 Kunneman M, Montori VM, Castaneda-Guarderas A, Hess EP. What is shared decision making? (and what it is not). Acad Emerg Med. 2016;23:1320–1324. 21 Durand MA, Barr PJ, Walsh T, Elwyn G. Incentivizing shared decision making in the USA—where are we now? Healthc (Amst). 2015;3:97–101. 22 Oshima Lee E, Emanuel EJ. Shared decision making to improve care and reduce costs. N Engl J Med. 2013;368:6–8.
Please cite this article as: A.Z. Paredes et al., Influence of english proficiency on patient-provider communication and shared decisionmaking, Surgery (2018), https://doi.org/10.1016/j.surg.2018.01.012
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23 van Roosmalen MS, Stalmeier PF, Verhoef LC, et al. Randomized trial of a shared decision-making intervention consisting of trade-offs and individualized treatment information for BRCA1/2 mutation carriers. J Clin Oncol. 2004;22:3293–3301. 24 Ludman E, Katon W, Bush T, et al. Behavioural factors associated with symptom outcomes in a primary care-based depression prevention intervention trial. Psychol Med. 2003;33:1061–1070. 25 Agency for Healthcare Research and Quality. MEPS-HC panel design and collection process. http://www.meps.ahrq.gov/mepsweb/survey_comp/hc_data_ collection.jsp. [Accessed November 17, 2017]. 26 Batalova J, Zong J. Language diversity and English proficiency in the United States. 2016. https://www.migrationpolicy.org/article/language-diversity-and-englishproficiency- united- states [Accessed November 28, 2017]. 27 2005 American community survey: place of birth by language spoke at home and ability to speak English in the United States; 2005. https://factfinder.census. gov/bkmk/table/1.0/en/ACS/05_EST/B06007. [Accessed November 28, 2017]. 28 U.S. Census Bureau. 2016 American community survey 1-year estimates: place of birth by language spoke at home and ability to speak English in the United States. 2016. https://factfinder.census.gov/bkmk/table/1.0/en/ACS/16_1YR/ B06007 [Accessed November 28, 2017]. 29 Barton JL, Trupin L, Tonner C, et al. English language proficiency, health literacy, and trust in physician are associated with shared decision making in rheumatoid arthritis. J Rheumatol. 2014;41:1290–1297. 30 Prohibition against exclusion from participation in, denial of benefits of, and discrimination under federally assisted programs on ground of race, color, or national origin. Title IV of the Civil Rights Act of 1964, 42 USCS § 20 0 0d; 1964. https://www.law.cornell.edu/uscode/text/42/20 0 0d. [Accessed November 28, 2017]. 31 Jacobs EA, Lauderdale DS, Meltzer D, Shorey JM, Levinson W, Thisted RA. Impact of interpreter services on delivery of health care to limited-English-proficient patients. J Gen Intern Med. 2001;16:468–474. 32 López L, Rodriguez F, Huerta D, Soukup J, Hicks L. Use of interpreters by physicians for hospitalized limited English proficient patients and its impact on patient outcomes. J Gen Intern Med. 2015;30:783–789. 33 Karliner LS, Jacobs EA, Chen AH, Mutha S. Do professional interpreters improve clinical care for patients with limited English proficiency? A systematic review of the literature. Health Serv Res. 2007;42:727–754.
34 Lee JS, Nápoles A, Mutha S, et al. Hospital discharge preparedness for patients with limited English proficiency: a mixed methods study of bedside interpreter– phones. Patient Educ Couns. 2018;101:25–32. 35 Lee LJ, Batal HA, Maselli JH, Kutner JS. Effect of Spanish interpretation method on patient satisfaction in an urban walk-in clinic. J Gen Intern Med. 2002;17:641–645. 36 Karliner LS, Pérez-Stable EJ, Gildengorin G. The language divide. The importance of training in the use of interpreters for outpatient practice. J Gen Intern Med. 2004;19:175–183. 37 Hornberger J, Itakura H, Wilson SR. Bridging language and cultural barriers between physicians and patients. Public Health Rep. 1997;112:410–417. 38 Reuland DS, Ko LK, Fernandez A, Braswell LC, Pignone M. Testing a Spanish-language colorectal cancer screening decision aid in Latinos with limited English proficiency: results from a pre-post trial and four month follow-up survey. BMC Med Inform Decis Mak. 2012;12:53. 39 Ai AL, Appel HB, Huang B, Lee K. Overall health and healthcare utilization among Latino American women in the United States. J Womens Health (Larchmt). 2012;21:878–885. 40 Valet RS, Gebretsadik T, Carroll KN, et al. Increased healthcare resource utilization for acute respiratory illness among Latino infants. J Pediatr. 2013;163:1186–1191. 41 De Jesus M, Xiao C. Predicting health care utilization among Latinos: health locus of control beliefs or access factors? Health Educ Behav. 2014;41:423–430. 42 Ai AL, Noël LT, Appel HB, Huang B, Hefley WE. Overall health and health care utilization among Latino American men in the United States. Am J Mens Health. 2013;7:6–17. 43 Carrasquillo O, Orav EJ, Brennan TA, Burstin HR. Impact of language barriers on patient satisfaction in an emergency department. J Gen Intern Med. 1999;14:82–87. 44 Darling C, Saczynski JS, McManus DD, Lessard D, Spencer FA, Goldberg RJ. Delayed hospital presentation in acute decompensated heart failure: clinical and patient reported factors. Heart Lung. 2013;42:281–286. 45 Comparative Effectiveness Research Translation Network’s Collaborative for Healthcare Research in Behavioral Economics and Decision Sciences (CERTAIN– CHOICES). Factors influencing delayed hospital presentation in patients with appendicitis: the APPE survey. J Surg Res. 2017;207:123–130.
Please cite this article as: A.Z. Paredes et al., Influence of english proficiency on patient-provider communication and shared decisionmaking, Surgery (2018), https://doi.org/10.1016/j.surg.2018.01.012