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Collection of Language Data and Services Provided by Health Plans
Elise H. Lawson, MD, MSHS; Rita Carreon, BS; German Veselovskiy, MPP; and Jose J. Escarce, MD, PhD

Objectives: Key stakeholders agree better data on patients’ language are needed to effectively address language-related barriers to timely, highquality healthcare. Our objective was to describe health plan efforts to collect language data from its members, provide language services, and improve the provision of culturally and linguistically appropriate services (CLAS).

 

Study Design: National surveys in 2003, 2006, and 2008.

 

Methods: Surveys were administered to health plans offering commercial, Medicaid, and/or Medicare Advantage products.

 

Results: 123 health plans responded to the 2008 survey (50% response rate), including 65 commercial (50%), 46 Medicaid (53%), and 12 Medicare plans (44%), representing a total enrollment of 133.8 million Americans. In 2008, 74.0% of health plans collected language data (commercial 60.0%, Medicaid 89.1%, Medicare 91.7%), which is an increase for each plan type since 2003. Health plans used direct and indirect collection methods. Nearly all health plans reported offering language services, the most common being telephonic interpreting, multilingual member materials, and access to bilingual providers. A variety of strategies for improving CLAS were cited by health plans, including improving health plan communication materials, health literacy initiatives for members, and targeted training for providers and staff.

 

Conclusions: Health plans have made substantial progress in the collection of language data and many are offering options for language services. With the rapid growth in Medicaid participation and newly insured individuals anticipated under the Affordable Care Act, health plans may be uniquely positioned to implement and test interventions that aim to improve appropriate utilization of language services by providers and patients.


(Am J Manag Care. 2011;17(12):e479-e487)

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Over the past several decades, the United States has experienced rapid growth in the racial and ethnic diversity of its population. By 2050, racial and ethnic minorities are estimated to comprise 54% of the nation’s population.1 Furthermore, in 2000, approximately 47 million Americans reported speaking a language other than English at home, and 21 million reported speaking English less than “very well.”2 Several studies have documented the negative impact of language barriers on patient-provider communication, patient safety, and the overall timeliness and quality of healthcare received.3-6

Although expanded insurance coverage is an important step in reducing gaps in care, it does not guarantee that patients, especially persons with limited English proficiency and low functional health literacy, can effectively navigate the healthcare system to access preventive services and obtain the care they need.7 Availability of a full range of culturally and linguistically appropriate healthcare services is essential for overcoming barriers and accessing timely care. To identify gaps in care for diverse populations, develop strategies to improve patient-provider communication, and allocate needed services and resources, key stakeholders agree that better data on patients’ language are needed.8
 
This article reports the results of 3 nationwide surveys of health plans regarding their efforts to improve the provision of culturally and linguistically appropriate services for their members.9-11 Specifically, we describe how health plans collect and use language data from their members, and what types of language access services are provided to members by plans. Our goal was to describe recent progress made by health plans and to identify areas needing further improvement.
 
METHODS
Data Sources
The sources of data for this study were surveys of health plans conducted in 2003, 2006, and 2008 by America’s Health Insurance Plans Foundation (AHIPF), with support from the Robert Wood Johnson Foundation. Reported results are primarily from the most recent survey (2008), although selected questions from the prior 2 surveys were used to identify trends over time. The target population was defined as health plans offering commercial, Medicaid, and/or Medicare Advantage products.

We developed the 2008 survey using input from an advisory group of health plans with expertise in data collection. We pilot tested the survey with 5 health plans and made revisions based on their feedback. The final survey instrument, consisting of 50 questions, had several sections. For this article, we used information on whether health plans collected data on the “primary” or “preferred” language of their members and how they collected these data. “Primary” and “preferred” language was not explicitly defined in the survey, as plans may utilize different definitions. The questions regarding how plans collected data focused on whether each used direct methods, defined as collection by the plan of self-reported data from its members; indirect methods, defined as collection of data from sources other than members; or both. We also used information on the provision of language access services for members and strategies employed by health plans for improving the provision of culturally and linguistically appropriate services (CLAS). Of note, these questions were asked of all plans regardless of whether or not they collected language data.

America’s Health Insurance Plans Foundation used health plans’ listings in the Atlantic Information Service’s (AIS) Directory of Health Plans for 2007 to develop the sampling frame for the survey, and excluded leased preferred provider organization (PPO) networks, subsidiary companies, plans that were no longer in business or had merged; plans with unknown enrollment; and very small plans (defined as commercial plans with <6500 members, Medicaid plans with <20,000 members, and Medicare plans with <5000 members). This resulted in a final sampling frame consisting of 245 health plans, all of which were invited to participate in the survey. For each plan, AHIPF used AIS data to identify the product with the highest enrollment and asked that responses be specific to that product. Because the commercial product has the highest enrollment for most health plans, 11 multiproduct health plans were asked to respond for 1 additional product, Medicaid or Medicare, so that the distribution of product-specific enrollment in the overall sample would reflect the composition of the industry.

The Excel-based survey was fielded via e-mail between June and October 2008. Prior to e-mailing the survey, AHIPF utilized multiple internal and external contact lists (eg, health plan staff responsible for addressing disparities within individual companies, chief medical officers, directors of quality improvement, etc) to identify the appropriate health plan representative to complete the survey. America’s Health Insurance Plans Foundation staff made several attempts to reach nonresponding plans and contacted submitters to clarify incomplete or unclear responses. On average, health plans completed the survey in approximately 1 hour.

A total of 123 health plans responded to the 2008 survey (50% response rate), including 65 commercial (50%), 46 Medicaid (53%), and 12 Medicare plans (44%). Response rates varied by plan size: 76% for large plans (enrollment >500,000 for commercial and >300,000 for Medicaid and Medicare plans); 64% for medium plans (enrollment 200,000-499,999 for commercial and 100,000-299,999 for Medicaid and Medicare plans); and 37% for small plans. Responding health plans represented a total enrollment of 133.8 million members.

The main methodological differences between the 2008 survey and the earlier 2003 and 2006 surveys included:

• In 2003, 83% of the health plans in the sampling frame were included in the survey sample via random selection, while in 2006 and 2008, 100% of the plans in the sampling frame were surveyed.

• In 2003 and 2006, all health plans were asked to respond on only 1 product.

• In 2003 and 2006, the survey was conducted via an e-mail invitation to health plans with a link to an Internet-based questionnaire.

• The 2003 and 2006 surveys asked about collection of “primary” language only.

• Overall response rates in 2003 and 2006 were 40% and 60%, respectively. As in 2008, large- and medium-size health plans were more likely than small plans to respond to the surveys.

Analysis
We calculated the proportions of health plans with various characteristics of interest. When appropriate, we weighted the proportions by plan enrollment. Because the responding health plans account for a large percentage of the sampling frame, we applied the finite population correction factor to obtain correct standard errors (SEs). In the Results section, all percentages are presented with the SE in parentheses.

RESULTS
Characteristics of Health Plans
The 2008 study sample included large, medium, and small health plans that were geographically distributed across all 4 US census regions, and that together represent a sizable percentage of the total US health plan enrollment (Table 1). Commercial plans that responded to the survey included health plans that offered health maintenance organization, PPO, and/or point of service products. Health plans in the study sample for 2003 and 2006 were similarly diverse in size, location, and product types.
 
Language Data Collection by Health Plans
Approximately 74.0% (SE, 2.8%) of health plans reported collecting language data (“primary” and/or “preferred”) for their members in 2008, including 60.0% (4.3%) commercial, 89.1% (3.2%) Medicaid, and 91.7% (6.3%) Medicare plans. This was an increase from 2003, when 38.5% (5.6%) of commercial, 84.6% (5.9%) of Medicaid, and 65.6% (6.5%) of Medicare health plans reported collecting primary language data (Figure). Most health plans that collected language data from their members also collected information on race and ethnicity.
 
Larger commercial and Medicaid plans were more likely to collect language data than medium or small health plans. For example, in 2008, 81.5% (4.0%) of large commercial plans collected these data, compared with 54.5% (10.1%) and 40.7% (7.8%) of medium and small plans, respectively. Similarly, 100% of large Medicaid plans reported collecting these data, compared with 93.3% (4.2%) and 83.3% (5.9%) of medium and small plans. When weighted by plan enrollment, 89.1% of commercial plan members, 96.8% of Medicaid plan members, and 95.3% of Medicare plan members were in health plans that collected some language data in 2008.
 
Health plans used both direct and indirect methods to obtain language data on their members. In 2008, the majority of commercial plans that collected language data relied on direct methods (66.7% [5.4%]) with only 2.6% (1.9%) reporting the sole use of indirect methods, and 30.8% (5.3%) reporting use of both data collection methods. By comparison, Medicaid and Medicare plans that collected language data used only direct methods less often (14.6% [3.9%] and 55.6% [13.4%], respectively), and only indirect data collection methods more often (24.4% [4.7%] and 22.2% [11.2%], respectively). Both methods were used by 61.0% (5.3%) of Medicaid plans and 22.2% (11.2%) of Medicare plans.
 
Health plans reported a variety of direct methods for collecting information on members’ language. However, the direct method most frequently reported by commercial and Medicare health plans as providing the most valuable data was having members self-identify their primary and/or preferred language during enrollment, which was used by 52.6% (5.8%) of commercial and 71.4% (14.2%) of Medicare plans that used direct methods. The direct method most frequently chosen by Medicaid plans as providing the most valuable data was obtaining language data directly from members during contacts with plan customer service agents, which was used by 90.3% (3.7%) of Medicaid plans that used direct methods. Other direct methods commonly used by commercial, Medicaid, and Medicare plans are reported in the upper panel of Table 2.

The indirect method most frequently cited by Medicaid and Medicare plans as providing the most valuable data was linking to files from external sources such as the Centers for Medicare & Medicaid Services (CMS) and state Medicaid agencies (Table 2). This method was used by 90.9% (3.5%) and 75.0% (19.8%) of health plans that collected indirect data, respectively. By contrast, the indirect method most frequently identified by commercial plans as providing the most valuable data was the use of geocoding software or obtaining data from the Consumer Assessment of Healthcare Providers and Systems survey, or another similar patient experience survey, which was used by 72.7% (10.2%) of plans. Surname identification software and geocoding software were used only by commercial plans and Medicare plans (Table 2).

Health plans were asked to name the top 5 primary or preferred languages, other than English, most commonly identified by members. Among plans that collected language data, the languages most frequently reported were Spanish (96.6%), Chinese (60.9%), Vietnamese (47.1%), Russian (24.1%), and Korean (21.8%). In all, 35 different languages were reported.

Reasons for Collecting Language Data
Health plans reported a variety of reasons for collecting language data from members. Commercial, Medicaid, and Medicare plans most frequently reported collecting these data to determine the need for translation of materials, such as summary plan descriptions, health education materials, and benefit materials (84.6% [4.2%], 87.8% [3.6%], and 100%, respectively). Commercial and Medicaid plans also frequently reported collecting these data to determine the need for interpreter services (61.5% [5.6%] and 61.0% [5.3%], respectively), whereas Medicare plans more often reported collecting data to hire staff that speak languages spoken by members (70.0% [11.7%]).
 
Language Access Services
All Medicaid and Medicare plans and 96.9% (1.6%) of commercial plans reported offering language access services to their members, regardless of whether they collected language data. Services commonly offered by commercial plans included telephonic interpreting (90.5% [1.6%]), multilingual member materials (68.3% [4.2%]), and access to bilingual providers (65.1% [4.3%]) (Table 3). Commercial plans that collected language data reported offering a greater variety of language access services than commercial plans that did not collect these data. Medicaid and Medicare plans offered language access services at higher rates than commercial plans.
 
The majority of commercial plans that offered language access services cited members’ requests (72.6% [4.0%]) for language services as a primary factor in determining whether to provide communications or services in a language other than English. Medicaid and Medicare plans frequently cited this reason as well (60.9% [5.0%] and 75.0% [10.0%], respectively), although these plans also often reported that the decision to offer services was based on a regulatory requirement (65.2% [4.9%] and 50.0% [11.5%]).
 
Health plans used a variety of methods to inform their members about available language access services, such as member outreach, provider directory, Web sites, posted signs, call centers, or through individual employers at open enrollment. The most commonly cited methods used to educate members included member materials (eg, handbooks, brochures, newsletters, etc) and member interaction with customer service.

Strategies for Improving Culturally and Linguistically Appropriate Services
The most frequently cited strategy for improving CLAS was the development of culturally and linguistically appropriate health plan communication materials and tools (Table 4). Other frequently cited strategies included increasing the availability of language access services; health plan staff and provider/ clinician initiatives such as cultural competency training; health literacy initiatives that aim to improve member understanding of health information; improvements in workforce diversity; and participation in community coalitions.
 
This is the first study to report health plans’ efforts regarding the collection and use of data on members’ primary and preferred language and the provision of language access services. We found that health plans made considerable progress between 2003 and 2008 in the collection of language data. In 2008, more than 9 of 10 health plan members were in plans that collected language data.
 
Health plans collected members’ language preference in a variety of ways. Approximately one-third of commercial plans used both direct and indirect methods with only a small minority relying solely on indirect sources. In contrast, almost one-fourth of Medicaid and Medicare plans relied on indirect sources alone. Of note, the most frequent indirect source cited by Medicaid and Medicare plans was linked files from an external source, such as CMS or state Medicaid agencies, which generally collect self-reported language information directly from program beneficiaries and recipients. Although health plans may consider these sources to be less reliable and complete than if plans themselves collected the data directly from their members, this approach is likely to be much more accurate than surname analysis, which infers a person’s language preference based upon surname.12 Discussion with health plans on their use of indirect data revealed that surname analysis and geocoding, which in theory could be used to infer a person’s language from characteristics of the neighborhood where the person lives,12 are typically used to determine whether language access services are needed at the aggregate level, rather than to assign language preferences to individual members.

The AHIPF conducted in-depth follow-up interviews with staff from 15 plans that responded to the 2008 survey to better understand the challenges and opportunities they face regarding data collection. Plans chosen for interviews represented both “noncollecting” and “collecting” plans across several geographic regions, and interviewed staff were clinical department leads, from communications and/or marketing departments. These interviews revealed that health plans perceive substantial barriers to language data collection, including potentially negative reactions from members concerned about the reasons for data collection and inadequate information technology systems. To address these challenges, health plans have developed external advisory panels to assist in communicating with diverse populations, called for standardization of data categories for use in the healthcare sector, and invested in infrastructures designed to facilitate data collection.9,13

Our finding that nearly all health plans offer language access services such as telephonic interpreting, multilingual materials, access to bilingual providers, and multilingual nurse lines, is encouraging given the considerable evidence that language barriers adversely affect healthcare quality and contribute to health disparities for patients with limited English proficiency.14-16 At members’ request, health plans can schedule interpreters for members seeking such services during their doctor visits or provide access to telephonic interpreting during clinical visits.17-19 Some health plans are also pilot testing video interpreters in hospital settings and provider offices. Studies comparing the effectiveness and acceptability of these different language access services are limited. However, there is evidence that in-person professional interpretation is superior to ad hoc interpretation by untrained family members, friends, or staff, and that the quality of in-person, telephonic, and video interpretation is similar.20-23

Although health plans reported using a variety of methods to advise members of the availability of language access services, we do not have data on how often members know about or use these services. Interpreter services are underutilized by physicians24,25 despite evidence demonstrating that these services result in improved clinical outcomes, reduced disparities in utilization, and higher patient satisfaction among patients with limited English proficiency.15,16,23,24,26-28 Ultimately, language access services can only be beneficial if they are used.

The development of an organization’s infrastructure to make available language access services can be influenced by legislative and regulatory requirements as well as accreditation standards. For example, Title VI of the Civil Rights Act of 1964 forbids programs that receive federal funds from discriminating on the basis of race, color, or national origin. Programs that receive federal funding, such as Medicare and Medicaid, must ensure that activities are accessible to all persons who, as a result of national origin, are limited in their ability to communicate in the English language.29 Additionally, some states require health plans to assess language needs and to provide language access services to their members.30 While a handful of states provide matching funds to pay for language services, the ongoing economic crisis affecting state budgets may provide challenges to health plans, hospitals, and providers as they seek to sustain these efforts.4,31

Our study has several limitations. First, we did not examine in detail the extent of health plans’ efforts to provide language access services or improve the provision of culturally and linguistically appropriate services. Second, the survey did not elicit information on where language data and services ranked against other, potentially competing priorities for health plans. Third, the 2003 and 2006 surveys inquired about collection of “primary” language only, while the 2008 survey inquired about collection of the “primary” and/or “preferred” language of members. However, analysis of individual plan responses over time indicates that this is unlikely to be a significant source of error. Finally, although the questions were generally straightforward and requested factual information, we were unable to assess the validity of health plans’ responses to  the surveys.

Meeting the needs of individuals with limited English proficiency requires involvement of multiple stakeholders, including patients, providers, payers, and policy makers. Health plans have already made substantial progress in the collection of language data to inform this process and many are offering options for language services as well. The Affordable Care Act (ACA) of 2010 provides considerable encouragement to continue this trend. Health plans participating under the health insurance exchanges, established at the discretion of states to provide access and coverage to individuals and small businesses, will be required to provide information and services to members in a culturally and linguistically appropriate manner and will be incentivized to participate in activities to reduce disparities.32-34 In addition, the ACA authorizes the US Department of Health & Human Services to improve data collection efforts aimed at understanding health disparities by ensuring that federal surveys and programs collect and report data on race, ethnicity, sex, primary language, and disability status. With the rapid growth in Medicaid participation and newly insured individuals anticipated under the ACA, health plans may be uniquely positioned to implement and test interventions that aim to improve appropriate utilization of language services by providers and patients.
Take-Away Points

Key stakeholders agree that better data on patients’ language are needed to effectively address language-related barriers to timely, high-quality healthcare.

 

  • In 2008, 74.0% of health plans collected language data (commercial 60.0%, Medicaid 89.1%, Medicare 91.7%); an increase since 2003.

 

  • Health plans cited a variety of strategies for improving the provision of culturally and linguistically appropriate services and nearly all plans reported offering language services in 2008.

 

  • Health plans may be uniquely positioned to implement and test interventions that aim to improve appropriate utilization of language services.
Affiliation

Acknowledgments

The authors would like to thank Mei Leng, MS, for her assistance with data analysis. Ms Leng is affiliated with the David Geffen School of Medicine at the University of California, Los Angeles, and her time was supported through the Robert Wood Johnson Foundation Clinical Scholars Program. The authors also thank Claire B. Gibbons, PhD, MPH, Project Officer at the Robert Wood Johnson Foundation, and America’s Health Insurance Plans (AHIP) Foundation Project Director, Barbara D. Lardy, MPH, for their guidance and support. Information related to this study was presented in a poster session at the AcademyHealth’s Annual Research Meeting held on June 12- 14, 2011, in Seattle, WA.


Author Affiliations: From David Geffen School of Medicine (EHL, JJE), University of California, Los Angeles; America’s Health Insurance Plans (RC, GV), Washington, DC.

 

Funding Source: Support for this study was provided by a grant (#62295) from the Robert Wood Johnson Foundation. Additionally, Dr Lawson’s time was supported by the Robert Wood Johnson Foundation Clinical Scholars Program.

 

Author Disclosures: Drs Lawson and Escarce report receiving an honorarium from the America’s Health Insurance Plans (AHIP) Foundation to perform this work. Ms Carreón and Mr Veselovskiy report employment with AHIP and payment for involvement in the preparation of this manuscript from the foundation.

 

Authorship Information: Concept and design (EHL, RC, GV, JJE); acquisition of data (RC, GV); analysis and interpretation of data (EHL, GV, JJE); drafting of the manuscript (EHL, RC, GV, JJE); critical revision of the manuscript for important intellectual content (EHL, RC, JJE); statistical analysis (EHL, JJE); obtaining funding (RC); administrative, technical, or logistic support (EHL, RC); and supervision (JJE).

 

Address correspondence to: Rita Carreón, BS, Deputy Director, Clinical Strategies & Health Care Equity, America’s Health Insurance Plans, 601 Pennsylvania Ave, NW, South Building, Suite 500, Washington, DC 20004. E-mail: rcarreon@ahip.org.

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12. Elliott MN, Fremont A, Morrison PA, Pantoja P, Lurie N. A new method for estimating race/ethnicity and associated disparities where administrative records lack self-reported race/ethnicity [published online ahead of print May 12, 2008]. Health Serv Res. 2008;43(5p1):1722-1736.

 

13. US Department of Health & Human Services. The national health plan collaborative: overview of its origins, accomplishments, and lessons learned. Final report. AHRQ Publication No. 09-0078-EF. September 2009. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/about/evaluations/nhpceval/.

 

14. Smedley BD, Stith AY, Nelson AR, eds. Unequal treatment: confronting racial and ethnic disparities in healthcare. Washington, DC: The National Academies Press; 2002.

 

15. Jacobs E, Chen AH, Karliner LS, Agger-Gupta N, Mutha S. The need for more research on language barriers in health care: a proposed research agenda. Milbank Q. 2006;84(1):111-133.

 

16. Flores G. The impact of medical interpreter services on the quality of health care: a systematic review. Med Care Res Rev. 2005;62(3):255-299.

 

17. Anthem Blue Cross and Blue Shield. Caring for diverse populations: a toolkit for physicians and health care professionals. http://www.clashealth.org/resourcelibrary-result.html?ResourceID=57. Published October 2005. Accessed November 2011.

 

18. Robert Wood Johnson Foundation. Hablamos juntos: improving patient provider communication for Latinos. Los Angeles, CA: Hablamos Juntos National Program Office; October 2007. http://www.rwjf.org/files/research/DCC.final.pdf. Accessed November 2011.

 

19. Robert Wood Johnson Foundation. Toolkit to reduce racial & ethnic disparities in health care: national health plan collaborative. http:// www.rwjf.org/files/research/nhpctoolkit.pdf. Published September 2008. Accessed November 2011.

 

20. Nápoles AM, Santoyo-Olsson J, Karliner LS, O’Brien H, Gregorich SE, Pérez-Stable EJ. Clinician ratings of interpreter mediated visits in underserved primary care settings with ad hoc, in-person professional, and video conferencing modes. J Health Care Poor Underserved. 2010;21(1):301-317.

 

21. Jones D, Gill P, Harrison R, Meakin R, Wallace P. An exploratory study of language interpretation services provided by videoconferencing. J Telemed Telecare. 2003;9(1):51-56.

 

22. Flores G, Laws MB, Mayo SJ, et al. Errors in medical interpretation and their potential clinical consequences in pediatric encounters. Pediatrics. 2003;111(1):6-14.

 

23. Garcia EA, Roy LC, Okada PJ, Perkins SD, Wiebe RA. A comparison of the influence of hospital-trained, ad hoc, and telephone interpreters on perceived satisfaction of limited English-proficient parents presenting to a pediatric emergency department. Pediatr Emerg Care. 2004;20(6):373-378.

 

24. Baker DW, Parker RM, Williams MV, Coates WC, Pitkin K. Use and effectiveness of interpreters in an emergency department. JAMA. 1996;275(10):783-788.

 

25. Diamond LC, Schenker Y, Curry L, Bradley EH, Fernandez A. Getting by: underuse of interpreters by resident physicians. J Gen Intern Med. 2009;24(2):256-262.

 

26. 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(2):727-754.

 

27. Morales LS, Elliott M, Weech-Maldonado R, Hays RD. The impact of interpreters on parents’ experiences with ambulatory care for their children. Med Care Res Rev. 2006;63(1):110-128.

 

28. Galbraith AA, Semura JI, McAninch-Dake RJ, Anderson N, Christakis DA. Language disparities and timely care for children in managed care Medicaid. Am J Manag Care. 2008;14(7):417-426.

 

29. Guidance to federal financial assistance recipients regarding title VI prohibition against national origin discrimination affecting limited English proficient persons [45 CFR 80.3(b)(2)]. US Department of Health & Human Services, Office of Civil Rights; August 2003. http://www.hhs.gov/ocr/civilrights/resources/laws/revisedlep.html. Accessed November 2011.

 

30. Second biennial report to the legislature on language assistance. California Department of Managed Care; July 2011. http://www.dmhc.ca.gov/library/reports/news/11rpt2legisla.pdf. Accessed November 2011.

 

31. Testimony of NHeLP’s Mara Youdelman. Congressional Asian Pacific American Caucus. http://www.healthlaw.org/index.php?option=com_content&view=article&id=341%3Atestimonynhelp-mara-youdelman-congressional-asian-pacific-americancaucus&catid=45&Itemid=196. Published July 2003. Accessed November 2011.


32. Somers SA, Mahadevan R. Health literacy implications of the Affordable Care Act. Center for Health Care Strategies, Inc. http://www.chcs.org/usr_do /Health_Literacy_Implications_of_the_Affordable_Care_Act.pdf. Published November 2010. Accessed November 2011.


33. US Department of the Treasury, Department of Labor, Department of Health and Human Services. Interim final rules for group health plans and health insurance issuers relating to internal claims appeals and external review processes under the Patient Protection and Affordable Care Act. Federal Register. 2010;75(141):43329-43364.

 

34. US Department of Health and Human Services. The Center for Consumer Information & Insurance Oversight. Interim procedures for internal claims and appeals under the Patient Protection and Affordable Care Act. US Department of Health and Human Services, Office of Consumer Information and Insurance Oversight. http://cciio.hhs.gov/ resources/files/interim_procedures_for_internal_claims_and_appeals.pdf. Published September 20, 2010. Accessed November 2011.


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