4
Defining Language Need and Categories for Collection

Data on a person’s language and communication needs should be part of any minimum data set related to health care delivery and quality improvement. The subcommittee recommends identifying spoken language need by determining first how well an individual believes he/she speaks English and then what language he/she needs for a health-related encounter. The subcommittee defines limited English proficiency (LEP) in the health care context as speaking English less than very well. To simplify the collection of language data, most entities should develop a list of common languages used by their service population, accompanied by an open-ended response option for those whose language does not appear on the list. When an entity has the capacity to collect additional information, the language preferred for written materials and the language spoken at home are also valuable. Locally relevant lists of language categories should be derived from a national standard list, with coding to facilitate information flow across entities.

The collection of data on the language needs of patients is important to improving health and health care. Collection of these data is necessary to meet legal obligations based on federal funding aimed at ensuring equitable access to health services and preventing discrimination based on national origin or limited ability to speak English. More important in the present context, however, knowledge of which patients have limited English proficiency (LEP) and of what their language needs are allows medical services and related interventions (e.g., provision of language assistance services, outreach, educational activities, translation of documents) to be targeted with the aim of improving the quality of care and reducing disparities. Not all persons with LEP are foreign born; more than one in four people aged 5 and over with LEP are born in the United States, and many more are naturalized citizens or documented immigrants (U.S. Census Bureau, 2003d; Youdelman, 2008).

Evidence on variations in health outcomes, medical errors, and receipt of quality health care as a function of English-language ability is persuasive that disparities exist, as reviewed in this chapter. Lack of English proficiency is a barrier not just to effective communication with individual health care providers, but also to accessing care in the first place. A review of the evidence base in this area convinced the subcommittee that the collection of data on language and communication needs is essential to safe, accessible, and effective, quality health care.

The subcommittee reviews various approaches to the collection of language data for health care improvement purposes. These approaches include practices of the U.S. Census Bureau because its data can easily be accessed to identify the spoken languages most often in use in a given geographic area, as well as a local population’s



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4 Defining Language Need and Categories for Collection Data on a person’s language and communication needs should be part of any minimum data set related to health care delivery and quality improvement. The subcommittee recommends identifying spoken language need by determining first how well an individual believes he/she speaks English and then what language he/she needs for a health-related encounter. The subcommittee defines limited English proficiency (LEP) in the health care context as speaking English less than very well. To simplify the collection of language data, most entities should develop a list of common languages used by their service population, accom - panied by an open-ended response option for those whose language does not appear on the list. When an entity has the capacity to collect additional information, the language preferred for written materials and the language spoken at home are also valuable. Locally relevant lists of language categories should be derived from a national standard list, with coding to facilitate information flow across entities. The collection of data on the language needs of patients is important to improving health and health care. Collection of these data is necessary to meet legal obligations based on federal funding aimed at ensuring equitable access to health services and preventing discrimination based on national origin or limited ability to speak English. More important in the present context, however, knowledge of which patients have limited English proficiency (LEP) and of what their language needs are allows medical services and related interventions (e.g., provision of language assistance services, outreach, educational activities, translation of documents) to be targeted with the aim of improving the quality of care and reducing disparities. Not all persons with LEP are foreign born; more than one in four people aged 5 and over with LEP are born in the United States, and many more are naturalized citizens or documented immigrants (U.S. Census Bureau, 2003d; Youdelman, 2008). Evidence on variations in health outcomes, medical errors, and receipt of quality health care as a function of English-language ability is persuasive that disparities exist, as reviewed in this chapter. Lack of English proficiency is a barrier not just to effective communication with individual health care providers, but also to accessing care in the first place. A review of the evidence base in this area convinced the subcommittee that the collection of data on language and communication needs is essential to safe, accessible, and effective, quality health care. The subcommittee reviews various approaches to the collection of language data for health care improvement purposes. These approaches include practices of the U.S. Census Bureau because its data can easily be accessed to identify the spoken languages most often in use in a given geographic area, as well as a local population’s 9

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94 RACE, ETHNICITY, AND LANGUAGE DATA proficiency with the English language. Additional guidance from the experiences of physicians, hospitals, health plans, states, and advocacy groups informed the subcommittee’s deliberations. Issues surrounding the collection of language data include understanding whether there is demand for language services in the health care sector (e.g., among hospitals, physicians) and across states, whether data should be collected for both spoken and written language needs, what languages would make up a national standard set of categories, and how those languages should be coded for sharing of data beyond a single service site. It should be noted that the subcommittee’s defini - tion of language is one that is inclusive of communication needs such as sign language. This chapter begins by reviewing what is known about the role of language in the provision of quality health care and health outcomes. It then summarizes estimates of populations needing language assistance and applicable legislation and regulatory requirements. Next is a discussion of various approaches used to question patients about their language needs. Language categories to be used by health care entities to collect these data and possible code sets are then considered. THE ROLE OF LANGUAGE IN HEALTH AND HEALTH CARE Interactions with Patients Needing Language Assistance The number of people nationwide needing language assistance is growing rapidly (Shin and Bruno, 2003), and individuals with these needs interact with the health care system daily. The extent of this interaction is revealed by recent surveys on encounters with LEP patients in hospitals, physician offices, and community health centers: • Eighty percent of hospitals provide services to LEP patients regularly, and 63 percent of hospitals encounter these patients daily or weekly (Hasnain-Wynia et al., 2006); • Eighty-one percent of general internal medicine physicians commonly treat LEP patients (54 percent at least once a day or a few times a week; 27 percent a few times a month) (American College of Physicians, 2007);1 and • Eighty-four percent of federally qualified health centers provide clinical services each day to LEP patients— 45 percent see more than 10 LEP patients per day; 39 percent see from one to 10 per day (National Asso - ciation of Community Health Centers, 2008). One study of hospitals indicated that 80 percent of hospitals have a health information technology (HIT) field dedicated to collection of language names, primarily to identify the languages needed for interpreter services (Regenstein and Sickler, 2006). Health care entities use a number of different approaches to collect this informa - tion: some limit the response categories to English, Spanish, and an “other language” category, while others offer respondents 200–300 languages from which to choose (Regenstein and Sickler, 2006; Tang, 2009). A study of the practice of internal medicine physicians found that only 28 percent kept detailed records of primary language needs, and about two-thirds of those who did record this information did so on paper rather than in a data system (American College of Physicians, 2007). By contrast, Kaiser Permanente, a health plan and a service provider covering eight states, began collecting data in 2009 in its electronic health record (EHR) system using a list of 131 spoken languages and 119 written languages (Tang, 2009). Health care entities may serve LEP patients by using bilingual health care providers; other bilingual staff trained in medical terminology; or, frequently, ad hoc interpreters, such as family members or bilingual staff with no knowledge of medical terminology. The latter approach is particularly prone to error (Flores, 2005, 2006b). Telephone interpretation services are also available from numerous sources; more than 200 different languages are offered by some interpretation and translation services (ASIST Translation Services, 2009; Language Line Ser - vices, 2009). Depending on the diversity of the population served, an entity may encounter persons with language assistance needs in just a few or many languages. New York Presbyterian Hospital, for example, reports providing interpretation in 95 languages (NQF, 2009). Reimbursement for the provision of interpretation and translation 1 12 percent of active patients in overall practice.

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9 DEFINING LANGUAGE NEED AND CATEGORIES FOR COLLECTION BOX 4-1 Language Concordance Between Patients and Providers Being able to speak to patients in their own language breaks down barriers, and some entities try to assign patients to language-concordant providers whenever possible. A growing body of literature finds that language concordance between patients and providers (i.e., both speak the patient’s primary language well) results in greater patient understanding, leading to increased satisfaction (Green et al., 2005; Ngo- Metzger et al., 2007), better medication adherence (Manson, 1988), greater understanding of diagnoses and treatment (Baker et al., 1996a), greater well-being and better functioning for persons with chronic disease (Perez-Stable et al., 1997), and more health education (Eamranond et al., 2009; Ngo-Metzger et al., 2007). When providers and patients are language discordant, some but not all effects can be mitigated by having trained interpreters (e.g., health education improves but not ratings of interpersonal care) (Ngo- Metzger et al., 2007). To ensure qualified interpreters or fully fluent providers, there has been movement toward training and certifying interpretation staff and ensuring the bilingual and cultural competence of providers (Cooper and Powe, 2004; Kettrick, 2008; Moreno et al., 2007; Youdelman, 2008). services is not always available (e.g., not under Medicare, or when states elect not to provide a match for Med - icaid funding for such services) (Bagchi and Stevens, 2006; Chen et al., 2007; Ku and Flores, 2005; Minnesota Department of Health Office of Rural Health Primary Care, 2008; Ponce et al., 2006b; Youdelman, 2007). Reau - thorization of the Children’s Health Insurance Program (CHIP) in 2009 increased federal matching for language services from 50 to 75 percent.2 An analysis of the adequacy of different means of providing language services and the funding of such services is beyond the scope of this report, but the issues have been examined by others (Gany and Ngo-Metzger, 2007; Karliner et al., 2007; Saha and Fernandez, 2007). Too often, either ad hoc or no interpretation services are available when LEP individuals seek health care services. There are no good estimates of how many LEP patients who need interpretation services fail to receive them, but a figure of nearly 50 percent was found in one emergency room study (Baker et al., 1996a). Uses of Language Data Entities that collect language data may use the data in various ways. The most obvious ways are to provide direct language assistance during a clinical encounter and information for follow-up care, such as chronic disease management education or discharge instructions in a patient’s language. Categorical data on demand for language assistance can inform hiring of bilingual staff or arrangements for interpretation services. An entity also might want to make appointments for patients with providers who are language concordant (Box 4-1). A hospital might want to track whether patients who receive language assistance have better outcomes on quality metrics compared with those who do not receive those services, or it might want to track whether those services are timely (Box 4-2). Language data also are useful for determining the need for translated materials; for example, Kaiser Permanente translated its Health Care Glossary into six languages to communicate commonly used terms and explanatory information about tests or conditions more effectively (NCQA, 2007). The California Healthy Families program indicates in which languages health plans have written materials on coverage, medical care reminders, member handbooks, and newsletters (California Healthy Families, 2008b). Additionally, the profile of patients being served can be compared with the population statistics of the ser- vice area to identify populations not being served. Yet while evidence shows that some health care entities col - lect language data on their patients, most entities fail to use these data to assess how language barriers impact 2 Children’s Health Insurance Program Reauthorization Act of 2009, Public Law 111-3, 111th Cong., 1st sess. (February 4, 2009).

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96 RACE, ETHNICITY, AND LANGUAGE DATA BOX 4-2 Assessing Whether Language Assistance Needs Are Met The Speaking Together: National Language Services Network program engaged 10 hospitals with di- verse patient populations to examine how to improve the quality and availability of health care services for LEP patients. According to Director Marsha Regenstein, “Screening for preferred language is a fundamental component in any measurement strategy related to quality improvement in language services.” Screen- ing for language service needs proved less difficult than linking data to patient care needs and assessing timeliness of services. Some possible performance metrics emerged from the program, including percent- age of patients who have been screened for preferred spoken language and percentage of patients with language needs who receive an initial assessment and discharge instructions from assessed and trained interpreters or bilingual providers. Cambridge Health Alliance took advantage of its EHR system to identify whether an interpreter was used, the time the interpreter spent, and the types of activities in which he/she engaged with patients (e.g., encounters with physician, informed consent, teaching, patient discharge). Another hospital tracked the increasing portion of patients who were screened for depression in their own language. Speaking Together, sponsored by The Robert Wood Johnson Foundation, offers a toolkit that details additional promising prac- tices and lessons learned in implementation; see www.speakingtogether.org. SOURCES: Regenstein, 2009; Regenstein and Sickler, 2006; RWJF, 2008. the quality of care and ultimately patients’ health status (Regenstein and Sickler, 2006). It should be noted that recommendations on which specific quality improvement actions should be undertaken by entities is beyond the subcommittee’s charge. Effect of Language on Health Status, Access to Care, Health Outcomes, and Patient Safety It is well established that LEP patients encounter significant disparities in access to health care (Hu and Covell, 1986; Weinick and Krauss, 2000), decreased likelihood of having a usual source of care (Kirkman-Liff and Mondragon, 1991; Weinick and Krauss, 2000), increased probability of receiving unnecessary diagnostic tests (Hampers et al., 1999), and more serious adverse outcomes from medical errors (Divi et al., 2007) and drug complications (Gandhi et al., 2000).3 The evidence also suggests that language barriers can increase the likelihood that patients will miss appointments, make less use of preventive care (Brach et al., 2005; Ku and Flores, 2005), or feel dissatisfied with health care services (Carrasquillo et al., 1999; Weech-Maldonado et al., 2003). On the basis of the findings detailed below, the subcommittee concludes that assessing language needs for each individual is an essential first step toward ensuring effective health care communication, and that provision of language assistance services is an actionable quality improvement option. 3 Search terms in PubMed included “health care quality,” “limited English proficiency,” “language barrier,” and “health care disparity.” Selected articles from this review are cited due to space limitations. Few studies were identified that reported no language proficiency effects, suggesting the possibility that the literature base itself is biased toward reporting positive effects. The few studies reporting no effects had methodological issues (Enguidanos and Rosen, 1997; Estrada et al., 1990; Stone et al., 1998).

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9 DEFINING LANGUAGE NEED AND CATEGORIES FOR COLLECTION Effect of Language on Health Status A growing literature documents a link between language barriers and poor quality health care (Pippins et al., 2007; Woloshin et al., 1995) that can lead to lower health status (DuBard and Gizlice, 2008). Research also indicates that this link can be broken by the use of interpreters. For example, use of interpreters is associated with improvements in the rate of follow-up visits after a visit to the emergency department (Karliner et al., 2007), in prescriptions written and filled (Flores et al., 2005), and in the need for obstetrical interventions. Many studies that do not directly evaluate how language barriers impact health status examine how language incompatibility or LEP leads to different medical management than that received by patients who do not have these limitations or are provided with interpreters (Bard et al., 2004; Bernstein et al., 2004; Sarver and Baker, 2000; Waxman and Levitt, 2000). For example, LEP patients who needed but did not receive interpreter services expe - rienced less satisfaction with their health care interactions, including less friendliness, time spent, and perceived concern for the patient, than those provided with or not needing interpreters (Baker, 1998). Recent studies have also revealed how language barriers can result in delays in prehospital care (Grow et al., 2008), less social interaction between dental staff and LEP patients (Hammersmith and Lee, 2008), and more negative clinical experiences in health care settings (Hampers et al., 1999) relative to non-LEP patients. One survey of care provided mainly in safety net hospitals found that the experiences of uninsured patients with access to an interpreter were comparable to or better than those of insured patients with no need for an interpreter (Andrulis et al., 2002). Moreover, families of non-English-speaking patients receive less information relevant to high-quality end-of life-care (Thornton et al., 2009). Such evidence suggests that language is a central factor in being able to achieve optimal health status and that bridging language gaps is essential to ensure quality care. Language barriers prevent providers from obtaining accurate patient histories, impair the ability to engage patients in joint patient–provider decision-making on treatment, and limit patients’ ability to obtain sufficient information for self-care (Wisnivesky et al., 2009). Poor patient–provider communication has been linked, for example, to poor asthma management practices in children (Chan et al., 2005) and in adults (Wisnivesky et al., 2009). It has also been associated with poor adherence to medication regimens (David and Rhee, 1998; Derose and Baker, 2000; Orrell et al., 2003) and concerns about unequal power dynamics between patients and providers (Schlemmer and Mash, 2006). Effect of Language on Access to Care Language barriers are closely linked to limitations in access to care (Wu et al., 2004) and to underuse of primary and preventive services (Woloshin et al., 1997), such as preventive cancer screenings (Jacobs et al., 2005; Ponce et al., 2006a), immunizations (De Alba and Sweningson, 2006; Sun et al., 1998), and routine check-ups (Pearson et al., 2008). In their examination of language-concordant and language-discordant patient–provider interactions in emergency services, Sarver and Barker (2000) discovered that the latter patients were less likely to receive follow-up appointments. LEP is also associated with lower rates of prescription medication use, ambulatory visits, dental visits, and appropriate mental health treatment (Brach et al., 2005; Derose and Baker, 2000; DuBard and Gizlice, 2008; Sentell et al., 2007). This lower use of services may be associated with feelings of being discriminated against, as well as lower levels of trust and less confidence in medical visits, for those with language barriers, noted in particular among older Latinos (Mutchler et al., 2007). Language barriers have also been closely related to patient-perceived quality of care; for example, 81 percent of English-speaking patients with colorectal cancer reported receiving high-quality care, compared with only 52 percent of non-English-speaking patients (Ayanian et al., 2005). The lower use of services by non-English speaking persons may also reflect the patient’s inability to articulate medical or mental health concerns to health care providers that are less easily measured by objective laboratory tests so that appropriate diagnoses can be made (Sentell et al., 2007). The inability to communicate with insurance personnel can also create difficulties in enrolling in a health plan (Feinberg et al., 2002), as well as in securing a usual source of care (Kirkman-Liff and Mondragon, 1991). One study, for example, found reduced enrollment of Medicaid-eligible children in publicly funded health insurance

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9 RACE, ETHNICITY, AND LANGUAGE DATA programs because of parental difficulties in understanding enrollment forms (Feinberg et al., 2002). Similarly, a study of LEP Medicare beneficiaries demonstrated poorer access to a usual source of care as compared with those who were not LEP (Ponce et al., 2006a). Research suggests that Spanish-speaking patients, as well as Spanish-speaking parents of pediatric patients, experience worse communication with their provider as compared with their English-speaking counterparts and less overall satisfaction with care (Jacobs et al., 2006). In one study, 89 percent of LEP Latinos who reported having a usual source of care cited the presence of interpreters or bilingual providers (Brach and Chevarley, 2008), implying that language capacity may be required to provide continuity of care for LEP patients. In addition, LEP patients who are seen by language-concordant providers demonstrate decreased likelihood of omitting medications and visiting the emergency department relative to those seen by language-discordant providers (Carter-Pokras et al., 2004; Manson, 1988). Tocher and Larson found no differences in meeting quality-of-care guidelines for LEP patients with diabetes (1998) or in the amount of time physicians spent with primary care patients (1999) in a setting with certified interpretation services available. Effect of Language on Health Outcomes Research has documented that poor health outcomes are more likely when language and cultural barriers exist between patients and providers (Anderson et al., 2003). Communication breakdowns occur when patients and pro - viders are language discordant (Baker et al., 1998; Karliner et al., 2004). Results from several studies (Marcos et al., 1973; Price and Cuellar, 1981) suggest that LEP patients provide more elaborate replies with greater disclosure when interviewed in their primary language and that conducting the assessment in the patient’s primary language may be particularly relevant for accurate diagnosis. The absence of language concordance between patient and provider and consequent reliance on ad hoc interpreters may impede disclosure of sensitive information (Marcos, 1979). It also negatively impacts comprehension of instructions and other treatment information necessary for adherence to and continuity of treatment (Wilson et al., 2005). Flores and colleagues (2005), for example, found that LEP patients who need but lack access to an interpreter have a poorer understanding of their medical diagnosis and treatment (Flores et al., 2005). Language also appears to impact health outcomes by influencing the quality of the patient–provider rela - tionship, including the development of trust, adherence to treatment, and follow-up (Rivadeneyra et al., 2000). LEP patients are more likely than those with good English-language proficiency to report inaccurate diagnoses, inadequate treatments, or negative health outcomes (Phelan and Parkman, 1995). Thus, if language barriers exist, diagnostic assessments, symptom disclosure, confidentiality, and treatment adequacy may be compromised (Baker et al., 1996b; Carrasquillo et al., 1999; Perez-Stable et al., 1997) and health outcomes suffer as a result. Effect of Language on Patient Safety Systematic literature reviews find that use of ad hoc interpreters is related to higher rates of communication errors and increased likelihood of clinical errors (Flores et al., 2005; Karliner et al., 2007). Family members and friends who act as ad hoc interpreters and do not understand the medical terminology involved or lack sufficient fluency in both languages are likely to interpret with errors (Flores et al., 2003). Typical errors include omissions, additions, condensations or abbreviations, substitutions, editorialization (interpreter adds or substitutes words that change the message), and false fluency (use of inaccurate words or phrases) (Flores et al., 2003). Flores and colleagues (2003) found that Spanish-speaking patients in an outpatient pediatric clinic experienced an average of 31 errors in medical interpretation by ad hoc interpreters and providers without sufficient language fluency, and more than half of these patients could have experienced negative adverse effects as a consequence of those errors. (It should be noted that, although research has documented a variety of interpretation errors during assessments, the clinical significance of such errors has not been well characterized.) Elderkin-Thompson and colleagues also found interpretation errors in more than 50 percent of videotaped encounters with nine Spanish-speaking nurses untrained in medical topics they were regularly called upon to interpret for LEP patients (Elderkin-Thompson et al., 2001).

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99 DEFINING LANGUAGE NEED AND CATEGORIES FOR COLLECTION Linguistic discordance can encompass differences in the concepts behind words and in the contexts giving meaning to those words (Flores et al., 2005). As a result, some researchers recommend that providers partner with trained interpreters who can bridge not only linguistic gaps but also cultural gaps that may challenge patient–pro - vider communication (Dohan and Levintova, 2007). Also of concern is that LEP patients without interpreters (compared with English-speaking patients and LEP patients with professional interpreters) receive fewer tests and procedures, which could lead to an increased risk for problems in the emergency department (Bernstein et al., 2004). Likewise, the lack of English language profi - ciency among the parents of pediatric patients has been correlated with a doubling of the risk of adverse medical events during pediatric hospitalizations (Cohen et al., 2005). In addition, LEP patients evidenced increased risk of misunderstanding prescription labels when seeing language-discordant providers compared with English-fluent patients (Wilson et al., 2005). Similarly, in one study, 27 percent of patients who needed but failed to receive interpreter services did not understand their medication instructions, compared with 2 percent who received such services (Andrulis et al., 2002).4 ESTIMATES OF POPULATIONS NEEDING LANGUAGE ASSISTANCE AND APPLICABLE REQUIREMENTS This section examines national estimates of the numbers of people in the United States whose primary lan - guage at home is not English and the portion who is not proficient in English who therefore may need language assistance during health care encounters. It also reviews applicable national legislative and regulatory requirements that may guide the collection of language-related data. Estimates of Populations Needing Language Services Census questions provide a starting point for determining the language needs of individuals in different geo - graphic areas through a comparable data set (Shin and Bruno, 2003). Since 1980, the Census has asked whether each person aged 5 years and older speaks a language other than English at home. This population doubled in absolute numbers from 1980 to 2000, and its percentage of the population over age 5 grew from 11 percent (23.1 million) in 1980 and 14 percent (31.8 million) in 1990 to 18 percent (47 million) in 2000 (Shin and Bruno, 2003). Respondents who speak a language other than English at home are also asked to enter the language they speak on an open-format response line and to rate their facility with spoken English (Figure 4-1). The same questions will be posed in Census 2010 and on the American Community Surveys. The Census asks no questions about reading or writing ability in English. Assessment of Limited English-Speaking Ability One simplified approach to assessing English-speaking ability is to ask people to rate themselves. The Census asks people to rate their ability to speak English on a scale from “very well” to “not at all” (see Figure 4-1). These ratings are based on self-defined and -perceived ability and not any specific test. Of the 47 million people aged 5 and older who reported speaking a language other than English at home on Census 2000, 55 percent reported speaking English “very well,” 22 percent “well,” 16 percent “not well,” and 7 percent “not at all” (Shin and Bruno, 2003). The proportion who spoke English very well was similar in 1980, when it was at 56 percent (Kominski, 1989). The criteria chosen to define LEP significantly affect the size of the LEP population. If LEP is defined as those who speak English less than “very well,” the Census 2000 LEP population numbers 21.3 million people over the age of 5 (more recent American Community Survey [ACS] LEP data estimate the total population at 23 million) (Youdelman, 2008). If it is defined as those who fall into the categories of “not well” and “not at all,” the LEP population numbers 10.9 million. The Census employs another measure called “linguistic isolation,” meaning that no one ages 14 or older in the household speaks English. This population of 11.9 million is similar in size to that 4 New York State requires translation and interpretation services by pharmacies (Office of the Attorney General, 2008).

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100 RACE, ETHNICITY, AND LANGUAGE DATA FIGURE 4-1 Census 2000 questions about language. SOURCE: Shin and Bruno, 2003. s Figure 4-1.ep bitmap image resulting from the more constrained LEP definition (Shin and Bruno, 2003). LEP individuals may have someone in their family that they can call upon when they need help with interpretation, but those in linguistically isolated households must look elsewhere for language assistance. Through schooling, children of immigrants eventually achieve a high degree of linguistic integration, and only a minority of immigrants’ grandchildren retains bilingualism (Alba, 2005). A larger proportion of young people (aged 5–17) than of those who are older, who live in homes where a non-English language is spoken, speak English “very well” (U.S. Census Bureau, 2003b, 2003c). Even among first-generation immigrants to the United States, most children develop English-speaking ability; for example, 79 percent of Mexican and 88 percent of Chinese first-generation children speak English “well” or “very well,” even while they continue to speak a language other than English at home (Alba, 2005). Thus, it is not surprising that children are often called upon to interpret for their parents and grandparents. As discussed above, however, the appropriateness of this arrangement for health care purposes has been questioned for several reasons, including the high frequency of errors with clinical conse - quences and the tendency to avoid sensitive and embarrassing subjects, such as those pertaining to sexual issues, domestic violence, abuse of drugs or alcohol, and the possibility of death (Flores, 2006a; McQuillan and Tse, 1995). Reflecting this concern, the California state assembly passed a bill in 2005 prohibiting the use of children under age 15 as medical interpreters; the bill was ultimately not enacted, however (EXODUS On-line, 2009). Effect of Being Foreign Born Being foreign born is not itself a marker for poor English skills: 39 percent of the 30.7 million foreign-born people aged 5 and over now living in the United States speak English “very well” and indeed may come from a country where English is spoken (e.g., Jamaica) (Grieco, 2003; Larsen, 2004; U.S. Census Bureau, 2003d). How - ever, about three-fourths of the 21.3 million people identified in Census 2000, who are LEP by a definition of speaking English “less than very well,” are foreign born; this accounts for 15.6 million people (U.S. Census Bureau, 2003d). More recent ACS data that estimate the LEP population at 23 million reveal that about 10.5 million are native born or naturalized citizens, and approximately 4 million more are documented immigrants (Youdelman, 2008). The proportion of the immigrant population that is proficient in English increases with time in the United States; for example, 36 percent of those in the country five years or less speak English very well, compared with more than 70 percent in the country for more than 30 years (Siegel et al., 2001). Proficiency is lower among low-wage workers and those with less than a high school diploma—population groups that might be more likely to access public programs (Capps, 2003). High school graduation rates among

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101 DEFINING LANGUAGE NEED AND CATEGORIES FOR COLLECTION the foreign-born populations from Europe and Asia now living in the United States are comparable to those among persons born in the United States—around 85–87 percent. However, the rate is much lower for immigrants from Central America, at 37.7 percent (Larsen, 2004). This is important because more than one-third of the U.S. foreign- born population comes from this region, particularly Mexico (Malone et al., 2003). Low literacy can compound the effect of a lack of English proficiency on understanding health-related information (Downey and Zun, 2007; Sudore et al., 2009; Zun et al., 2006). Applicable Legal Requirements Civil Rights Act Requirements to Identify the Service Population Title VI of the Civil Rights Act of 1964 prohibits discrimination on the basis of race or national origin by those who receive federal funds: No person in the United States shall, on the ground of race, color, or national origin, be excluded from participation in, be denied the benefits of, or be subjected to discrimination under any program or activity receiving Federal financial assistance.” {42 U.S.C § 2000d} Language needs have been considered a factor in deciding discrimination cases based on national origin under Title VI5 (Chen et al., 2007) and in determining whether there have been violations of equal access for language minorities under the Voting Rights Act.6 Settlements have resulted in requirements to collect localized and granu- lar data directly from those receiving services or indirectly through data descriptive of the service area (HHS, 2009c). HHS’ Office for Civil Rights (OCR) states that HHS is “committed to enhancing access to HHS services by LEP persons and closing the health care gap” (HHS, 2009b). Language assistance is to be made available at all points of contact with federally funded programs—enrollment, registration, and direct medical services. HHS describes LEP persons more broadly than the Census questions, which focus on spoken English. For HHS, LEP includes persons: • Who “are unable to communicate effectively in English because their primary language is not English and they have not developed fluency in the English language.” • Who “may have difficulty speaking or reading English.” • Who “will benefit from an interpreter who will translate to and from the person’s primary language.” • Who “may also need documents written in English translated into his or her primary language so the person can understand important documents related to health and human services” (HHS, 2009a). Executive Order 13166, Improving Access to Services for Persons with Limited English Proficiency, requires each federal agency to review its services and develop and implement reasonable steps by which LEP persons can have “meaningful access” to programs or activities without charge for language services (Executive Office of the President, 2000). The guidance seeks to clarify the obligations of recipients of federal funds to provide language assistance services. Additionally, LEP persons are to be notified that free interpretation services are available so that they can make an informed choice about whether to use a friend or family member as an interpreter instead. HHS Title VI Civil Rights guidance allows patients to choose whether to use a language service. But interpreter services still must be provided if good medical practice might be compromised, the competence of the family interpreter is in question, or issues of confidentiality or conflicting interests arise. The emphasis is on voluntary compliance with these provisions. The Department of Justice issued four Title VI “balancing factors” to be applied across all federal agency– funded programs: the number or proportion of LEP persons in the service population, the frequency of contacts, 5 Lau v Nichols, 414 U.S. 563 (1974). 6 Department of Justice. 42 U.S.C. Chapter 20 § 1973aa-1a. The Public Health and Welfare Act, Elective Franchise.

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102 RACE, ETHNICITY, AND LANGUAGE DATA the importance of the services to the persons’ lives, and the resources available to support services (U.S. Depart - ment of Justice, 2002). HHS subsequently revised its guidance accordingly (HHS, 2009b). Yet lack of knowledge of the requirements by both providers and patients or of willingness of LEP patients to pursue complaints when faced with language barriers leaves many persons without meaningful access to health care, and few states have comprehensive laws mirroring the federal requirements (Chen et al., 2007; Perkins and Youdelman, 2008). Requirements of the Americans with Disabilities Act Communication needs extend beyond spoken language capability to include barriers imposed by disabilities affecting hearing, speech, and vision. The Americans with Disabilities Act (ADA) of 1990 and Section 504 of the Rehabilitation Act of 1973 address nondiscrimination on the basis of such disabilities. Resolution of legal cases has resulted in requiring the availability of qualified sign language interpreters within a certain time frame (e.g., 2 hours) and the use of other auxiliary aids, such as TTY or TDD, 7 in venues such as hospitals (HHS, 2009c; U.S. Department of Justice, 2003). Further examples of the types of auxiliary aids or services that might be required to ensure accommodation of a person with a disability are outlined in regulations. 8 There are an estimated 1 million functionally deaf persons in the United States (Mitchell, 2005), and up to 36 million people have some degree of hearing loss (National Institute on Deafness and Other Communication Disorders, 2009). Only rough estimates―of 360,000 to 517,000 persons―exist of the number of deaf individuals who use sign language (Mitchell, 2005). Of note, immigrants who are deaf may have learned a different sign language from that taught in the United States (Gordon, 2005). State Laws States have instituted a number of additional laws to address language access. These are not reviewed in detail in this report. However, the status of laws nationally was recently reviewed by Perkins and Youdelman (Perkins and Youdelman, 2008), and Au and colleagues focused on activities in three states—California, Massachusetts, and New York (Au et al., 2009). These laws address the provision of direct language assistance, the setting of thresholds for applicable languages, continuing medical education requirements for physicians, the availability of interpreters for specific services (e.g., admissions to mental health facilities), facility licensure, and certification of interpreters. APPROACHES TO ELICITING LANGUAGE NEEDS The subcommittee considered different approaches to questions to elicit language needs. Assessment of English-language ability is widely used in studies evaluating the effects of language proficiency on disparities in the quality of health and health care (Jacobs et al., 2001). Table 4-1 lists approaches to questioning about patients’ language needs that are employed by some health care entities. Questions address the individual’s English profi - ciency, primary or preferred spoken language, language spoken at home, and preferred written language. English Proficiency An advantage of using a question to assess English proficiency, such as that used on the Census (Figure 4-1), is the ability to determine quickly whether a patient is likely to have language barriers that will limit his/her ability to navigate the health care system and communicate effectively with health care providers. Proficiency level data can be obtained for the entire population or matched to different languages (for example, among persons who speak a language other than English at home, 66 percent of Vietnamese speak English less than very well, compared with 23 percent of Hindi-speaking Asian Indians) (Kagawa-Singer, 2009; U.S. Census Bureau, 2003e). When an entity 7 TTY stands for TeleTYwriter or text telephone, and TDD is telecommunication device for deaf persons. 8 Department of Justice. 28 CFR Part 36 § 36.303. ADA Standards for Accessible Design (July 1, 1994).

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10 DEFINING LANGUAGE NEED AND CATEGORIES FOR COLLECTION TABLE 4-1 Summary of Question Types and Categories English Proficiency Question Examples: • How would you rate your ability to speak and understand English? (Hasnain-Wynia et al., 2007) • How well do you speak English? (Karliner et al., 2008) Categories: • Very well • Well • Not well • Not at all (Shin and Bruno, 2003) Spoken Language Question Examples: • What language do you feel most comfortable speaking with your doctor or nurse? (Hasnain- Wynia et al., 2007) • In what language do you prefer to receive your medical care? (Cambridge Health Alliance in RWJF, 2008b; Karliner et al., 2008) • What language do you want us to speak to you in? (California Healthy Families, 2008a) • What language do you prefer to speak when you come to the medical center? What language do you feel most comfortable speaking? (Tang, 2009) Categories: • Names of specific languages in use in the United States, approximately 600 categories Plus: • Other, please specify:____ • Sign language(s) Language Spoken at Home Question Examples: • What language do you speak at home? (Shin and Bruno, 2003) • What language(s) do you usually speak at home? (NCHS, 2009) • What is the primary language spoken at home? (Cambridge Health Alliance in RWJF, 2008b) Categories: • Names of specific languages in use in the United States • Census denominator available for many but not all languages Written Language Question Examples: • In which language would you feel most comfortable reading medical or healthcare instructions? (Hasnain-Wynia et al., 2007) • What language should we write to you in? (California Healthy Families, 2008a) • What is your preferred written language?a • In what language do you prefer to read health-related materials? (Cambridge Health Alliance in RWJF, 2008b) • What language do you prefer for written materials? (Tang, 2009) Categories: • Names of specific languages in use in the United States • Braille Mandated: • Threshold language categories may be required by law and applicable to an entity in different states a Health Care Language Assistance Act of 200, California S.B. 853 § 1367 (October 8, 2003). is considering which languages to list on its data collection instruments, knowing not just how many people speak a language but also their level of English proficiency and thereby their need for services will be helpful. Since the response is based on self-report, it is important to understand the question’s reliability in deter- mining proficiency. The Census Bureau does not define which level of ability represents LEP (Griffin and Shin, 2007). However, the Census Bureau field tested the question to assess the validity of responses. Respondents who indicated that they spoke English “less than very well” had difficulty with the tests administered in the English

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116 RACE, ETHNICITY, AND LANGUAGE DATA training, compliance monitoring, and translation of vital documents (CPEHN, 2008). 16 Specific tiered thresholds, with different combinations of plan enrollees and percentages and numerical thresholds, are established for the translation of documents: • “For health plans with a million or more enrollees: they must translate vital documents into the top two non-English languages, plus any language whose number of speakers in the plan is either 15,000 enrollees or greater, or totals 0.75% of the enrollee population. • For plans with 300,000 to one million enrollees: vital documents must be translated into the top non-English language plus languages whose speakers are 6,000 enrollees or 1% of the enrollee population. • For plans with less than 300,000 enrollees: vital documents must be translated into any language whose speakers total 3,000 enrollees or 5% of the enrollee population.” (CPEHN, 2008) In the Voting Rights Act, specific population thresholds are established to determine what constitutes a language-minority group and for whom documents must be translated (U.S. Census Bureau, 2002). The thresholds are defined as more than 10,000 persons, more than 5 percent of all voting-age citizens in a district, more than 5 percent of residents of an Indian reservation, or a locale where the illiteracy rate is higher than the national rate (U.S. Department of Justice, 2008). Examination of the effect of using a percentage threshold to identify which languages should be included as data collection categories at the state level reveals that significant subgroups would be omitted. For example, 815,386 people aged 5 and over speak Chinese at home in California (2.6 percent of the state population) but this percentage is far higher than the national figure of 0.7 percent (U.S. Census Bureau, 2003j). Application of a 5 percent threshold statewide in California would identify only Spanish, even though that state, with 39 percent of those aged 5 and over speaking a language other than English at home, is one of the most linguistically diverse states in the nation (U.S. Census Bureau, 2003j) and has a large LEP population, estimated at 6.3 million (U.S. Census Bureau, 2003i). Even a 1 percent population threshold in that state would make only Spanish, Chinese, Vietnamese, and Tagalog threshold languages for data collection. A 1 percent threshold applied to other states would for the most part yield only Spanish as a language to monitor (U.S. Census Bureau, 2003j). When applied to smaller geographic areas with more concentrated LEP populations, however, such percentages would yield additional language groups, and thresholds might be found useful for states or health plans in establishing the number of languages required for reporting and/or translation of materials. The size of the population served should influence any numerical threshold; the service populations for all of the different entities potentially affected by a recommendation of this subcommittee are too variable for a single threshold number of 1,000 or some other value to be applied. Therefore, and because available information on thresholds is set in the context of a specific intervention (provision of language assistance services or translation of documents), the subcommittee decided not to specify a threshold (e.g., number of persons or percent of population speaking a language) for determining which spoken or written languages should be used as response options or as categories in analysis by states or other entities for the purposes of health care quality improvement. The subcom - mittee believes that any numerical or percentage thresholds for purposes of requiring the delivery of services or the translation of documents would best be determined by appropriate regulatory, licensing, or accrediting bodies. Considerations for Modes of Data Collection While the goal is to identify the specific language needs of each individual to enable effective health care communications, having lists of 400 to 500 language categories is impractical for most data collection instruments, whether in paper or electronic form, unless electronic systems have more sophisticated software to reduce staff or patient time required to search for the correct category. Accordingly, many entities will have to construct lists of perhaps 10 to 20 language categories that will be manageable within the space constraints of their paper or elec - tronic data collection formats. These lists should always have an option to collect languages not listed by including 16 Health Care Language Assistance Act of 200, California S.B. 853 § 1367 (October 8, 2003).

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11 DEFINING LANGUAGE NEED AND CATEGORIES FOR COLLECTION an “Other, please specify: ____” choice so that data on any language needed by an individual can be collected. Such an approach was employed in one study to identify the languages used among school-age children. A state survey of LEP students included 13 prespecified languages on the collection form, with the opportunity to list other languages; the responses ultimately yielded 460 languages (Kindler, 2002). For intake systems that do not allow for writing in an “other” response, more detailed lists will be required, as simply reporting a large “other” category with no specific language identifiers is not useful for understanding the language needs of individual patients. An alternative to having a prespecified locally relevant list would be to include an open-response section on paper forms or computer input screens. Some find this approach desirable because a single free-response box takes up minimal space. For example, the California Healthy Family program uses an open-ended format that captures about 30 languages including American Sign Language.17 The main drawback is that it is generally more time-con- suming to enter each response manually into a database and to decipher handwriting on paper forms and spelling variations whether paper forms or computer input screens. The Census Bureau has the ability to scan optically or key in individually the free-response answers on language use (Shin and Bruno, 2003), but this is likely too costly an approach for many entities. Kaiser Permanente’s computerized registration pages incorporate keystroke recognition; as a clerk types in the first couple of letters, the computer responds with a short list of alternatives out of the 131 options in the full set of language options (Appendix G) (Tang, 2009). Contra Costa Health Plan uses a system in which typing the initial letter of a language brings up one of the most commonly encountered languages (top 15 languages), such that typing an “s,” for example, would bring up Spanish; if the desired response is not in the first grouping, a second keystroke on “s” will bring up Samoan and other selections (Appendix H). In sum, as a practical matter, most individual providers, plans, or states may want to have a limited list of language categories for collection based on the languages most common among their populations with LEP, taking into account as well as the space limitations of their paper forms or the capacity of their computer systems. Any prespecified list of response categories should also include the option of “Other, please specify: _____” to capture an individual’s language need when it does not appear on the list. Entities using open-format questions must make sure that responses are specific enough to be useful in planning services and in conducting analyses—for example, a response that says Asian language will not be specific enough to identify a language. DEVELOPMENT OF A NATIONALLY STANDARDIZED LIST OF LANGUAGE CATEGORIES Since effective patient–provider communication is central to patient-centered care and the overall quality of health care, knowing the language each individual needs to communicate effectively and to understand the care process is fundamental. The subcommittee sought to determine how many languages are in use in the United States to understand the scope of what might be encountered during a patient contact or visit. The subcommittee notes that any national list of languages ideally should have a common vocabulary of language names and unique codes for languages to facilitate data sharing. Every organization may not need to report language data to others, and thus may not need to participate in a uniform coding scheme or will be able to make a crosswalk from its own coding practices to a national standard set. Overall, however, comparability and interoperability will be enhanced by a coding system. The subcommittee has identified two major code sets for consideration: the Census Bureau and the International Organization for Standardization (ISO) 639 language code sets. National Standard List of Spoken Language As noted, the Census reports about 380 single languages, as well as several language groups (Scandinavian, American Indian, and African languages for general responses not captured by specific language names such as Norwegian or Navajo), with unique codes (Modern Language Association, 2009a; U.S. Census Bureau, 2007). 17Personal communication, E. Sanchez, California Managed Risk Medical Insurance Board, July 20, 2009. Languages include English (46.1 percent of applicants), Spanish (45.3 percent), Asian (6.3 percent, including Cantonese, Chinese, Korean, Mandarin and Vietnamese), and other languages (2.1 percent, including Russian, Farsi, Armenia, Tagalog, Arabic, Hmong, Japanese, Cambodian, Thai, Hebrew, Lao, Portuguese, Samoan, Polish, Turkish, French, Mien, Llacano, Italian, and American Sign Language).

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11 RACE, ETHNICITY, AND LANGUAGE DATA The subcommittee prepared a draft template of spoken languages in use in the United States, based on Census categories, and formal and informal reports from hospitals, community health centers, language assistance services, individual hospitals, and health plans. This compilation resulted in more than 650 languages or composite group - ings; however, a smaller number may be needed for effective communication in a health care context (i.e., the subcommittee identified 300 from its limited survey of health care entities). The resulting list of spoken languages (Appendix I) can serve as basis for finalizing a national standard list of languages. What defines a unique language versus a dialect? Linguistic scholars and those who speak a language do not always agree on what defines a distinctly unique language. For ISO 639, classification takes into account “linguistic similarity, intelligibility, a common literature,” and whether speakers of one language can understand the other. Even with this understanding, however, there may be other “well-established distinct ethnolinguistic identities [that] can be a strong indicator that they should nevertheless be considered to be different languages.” Thus, the ISO language lists and particularly their coding focus on distinct languages with distinct codes, whereas the Census Bureau is more likely to give related languages the same code. The ISO codes represent both spoken and written language names; separate script codes apply to written languages, as well, to describe their lettering (SIL International, 2009c). The names of numerous languages have multiple possible spellings, even between the Census Bureau and ISO 639 language lists, and patients may provide an alternative spelling as well. Languages might even be called slightly different names, such as Amish, Pennsylvania Dutch, or Pennsylvania German. This need not be a bar- rier to the list of choices developed locally as long as it is clear on a national standard list how to categorize the alternative spellings or names. The subcommittee did not generate a list of written languages, but illustrates these needs with the experiences of Kaiser Permanente (Appendix G) and Contra Costa Health Plan (Appendix H). ISO 15924 has four-letter script codes that can be appended to language names to distinguish how a language is written (e.g., use of Cyrillic [Cyrl], or Arabic [Arab] (Unicode ISO, 2009). Braille has the script code of Brai. Coding of Responses This section reviews approaches to coding the languages included on the Census and ISO/Ethnologue lists. Ethnologue studies the world’s living and ancient languages (living languages now number more than 6000) and updates the language lists every four years. The Census set includes about 380 three-digit numeric codes (e.g., Spanish 625, Russian 639, Thai 720) for the languages it tracks (U.S. Census Bureau, 2007). This set actually covers a greater number of languages, about 530, since as noted, the same code is used for multiple related languages; by comparison, the languages in this larger set have their own unique codes under the ISO 639-3 classification system. The Census codes underlie the extensive data available on language spoken at home and level of English proficiency among subgroups. The ISO codes have evolved from a first-generation two-letter coding system (ISO 639-1), to a three-letter system to accommodate additional languages primarily for bibliographic uses (ISO 639-2), to a set that now incorporates more three-letter codes to cover 6,000 languages (ISO 639-3). The ISO 639-3 codes are intended “to provide a comprehensive set of identifiers for all languages for use in a wide range of applications, includ - ing linguistics, lexicography and internationalization of information systems.” (Library of Congress, 2007; SIL International, 2009b). In some instances, the distinction among languages in the ISO coding system may be of less practical concern, but in other cases distinct coding may be necessary. For instance, the difference among German, Swiss German, and Austrian German will not matter for most analyses and quality improvement initiatives; these three languages have an identical code under the Census Bureau system (607), but are coded deu, bar, and gsw, respectively, under ISO 639-3. On the other hand, there are even cases in which very different languages have the same name but very different meanings; for example, the Census codes Mende as 793, 18 but one cannot know whether this is the Mende language of Sierra Leone (men) or of Papua New Guinea (sim) as distinguished by ISO 639-3. At the 18 Personal communication, H. Shin, U.S. Census Bureau, July 13, 2009.

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119 DEFINING LANGUAGE NEED AND CATEGORIES FOR COLLECTION local level, practitioners are likely to figure out the difference, but if it is desirable to aggregate such detail across multiple sites for various analytic purposes or to plan interventions, the more discrete codes may be better. Sorting the Chinese languages is particularly challenging for the lay person. Health Level 7 (HL7), a standards-setting organization for electronic health records, worked with Centers for Disease Control and Prevention (CDC) to develop the unique codes for use in the CDC/HL7 Race and Ethnic - ity Code Set 1.0 for ethnicities (CDC, 2000). HL7 has not yet adopted any codes for languages. In its incidental collection of information on languages, the subcommittee encountered more instances of use of the ISO coding scheme. For example, the Illinois Department of Human Services and Contra Costa Health Plan use the ISO 639- 1 two-letter alphabet code. Others are using the three-letter coding for tracking language needs and determining resources required to address them (e.g., the courts of New Jersey to identify persons who need interpreters and to plan for service enhancement; Anthem Blue Cross survey of language needs). 19 In conclusion, the subcommittee believes that there are advantages to both the Census Bureau and ISO coding schemes for languages. In the next chapter, the subcommittee indicates the need for HHS to consult with the Census Bureau, the registration authorities for the ISO codes, and others that establish unique coding for interoperability, such as HL7; the subcommittee itself does not endorse one coding scheme over another. If the Census coding approach were to be adopted, the subcommittee notes that the Census list of languages and codes would likely need some additional changes to be useful. Because of how the language question is asked on the Census (Does this person speak a language other than English? [Figure 4-1]), yes (language other than Eng - lish) and no (English only) are responses coded just 1 and 2, respectively; there is no unique three-digit code for English. Sign language, an important communication tool, is not a language response on the Census. By contrast, ISO-639 has unique codes for 130 types of sign languages (SIL International, 2009a), such as aed for Argentine Sign Language and ase for American Sign Language. As the Census Bureau does not have a specific code for sign language, it would code a response of American Sign Language as English for its purposes 20—an approach that is less helpful in responding to a person’s language needs in the health care environment. A separate category for noting which persons have speech loss has been useful for some entities to understand the communication needs of all patients. Further options for “declined,” “unavailable,” or “unknown” are also useful when data are being recorded to determine the portion of the service population from whom language data have been collected; the Census Bureau does not generally code for these options. Recommendation 4-3: When any health care entity collects language data, the languages used as response options or categories for analysis should be selected from a national standard set of lan - guages in use in the United States. The national standard set should include sign language(s) for spoken language and Braille for written language. SUMMARY The subcommittee has reviewed the frequency of health provider interactions with people needing language assistance and the impact of limited English proficiency on access to care, health outcomes, and patient safety. An estimated 21.3 to 23.0 million people in the United States would meet the subcommittee’s definition of LEP for health care purposes—self-assessment as speaking English less than very well. The subcommittee has established a hierarchy of questions to ask about the language variable, with the highest emphasis on establishing language need based on two questions—a person’s rating of their English language proficiency and the preferred language needed for health care interactions. The subcommittee’s task extended to exploring what a national standard list of language categories might look like. A number of approaches to designating languages for collection were considered, including whether there should be uniform collection nationwide of a limited number of categories or locally relevant lists chosen 19 During July 1, 2004, through June 30, 2005, interpretation was provided in Superior Court for 77 languages across 83,548 events, with 16 major languages accounting for most events (New Jersey Courts, 2009). 20 Personal communication, H. Shin, U.S. Census Bureau, July 13, 2009.

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120 RACE, ETHNICITY, AND LANGUAGE DATA by the individual data collection entity from a larger national list. A limited national list, whether of 10 languages or 40, would not be useful for every health care provider, state, or health plan. The subcommittee therefore favors the approach of allowing selection of locally relevant language categories from a national standard list, with a common category and coding framework. Local lists should provide an “Other, please specify: __” option in case an individual does not find a needed language on a collection instrument with check-off boxes or even if that lan - guage is not yet on the national standard list of names. Such a language list might need to be updated from time to time to accommodate new immigrant groups, and health care providers might encounter new names before a formal Census or ISO review takes place. 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