Literature DB >> 22823554

Exploring health plan perspectives in collecting and using data on race, ethnicity, and language.

Julie Gazmararian1, Rita Carreón, Nicole Olson, Barbara Lardy.   

Abstract

OBJECTIVES: To explore why health plans collect or forgo data collection efforts on race, ethnicity, and language (REL), and the challenges encountered in collecting and using data for quality improvement. STUDY
DESIGN: In-depth interviews with 15 health plans were conducted between June and August 2009.
METHODS: Fifteen health plans participated and were divided into 2 groups: Plans that collect and use REL data (n = 10), and plans that do not collect REL data (n = 5). A structured interview guide was developed that included questions about REL data collection efforts, leadership support, collaboration with external partners, and challenges and opportunities in the collection and use of REL information. For plans not collecting REL data, questions were also asked regarding reasons to forgo data collection and existing health equity efforts. A summary report, based on audiotapes, interview notes, and input from the research team, was developed and analyzed.
RESULTS: The interviews highlight the need for new partnerships and coordinated efforts to improve healthcare equity through disseminating best practices and tools that help expand such activities. Barriers noted include the costs associated with adapting information technology systems to accommodate new functions, such as new data fields, appropriate software and analytical tools, and the lack of standard codes for race and ethnicity.
CONCLUSIONS: Health plans are eager to collaborate with new partners and share strategies to collect REL data as a foundation to reduce disparities. Opportunities exist to collaborate with employers and purchasers to improve the extent and quality of REL data and can ultimately lead to designing and implementing culturally appropriate programs in the workforce.

Entities:  

Mesh:

Year:  2012        PMID: 22823554

Source DB:  PubMed          Journal:  Am J Manag Care        ISSN: 1088-0224            Impact factor:   2.229


  4 in total

1.  Using the Bayesian Improved Surname Geocoding Method (BISG) to create a working classification of race and ethnicity in a diverse managed care population: a validation study.

Authors:  Dzifa Adjaye-Gbewonyo; Robert A Bednarczyk; Robert L Davis; Saad B Omer
Journal:  Health Serv Res       Date:  2013-07-16       Impact factor: 3.402

2.  Improving the Collection of Race, Ethnicity, and Language Data to Reduce Healthcare Disparities: A Case Study from an Academic Medical Center.

Authors:  Wei-Chen Lee; Sreenivas P Veeranki; Hani Serag; Karl Eschbach; Kenneth D Smith
Journal:  Perspect Health Inf Manag       Date:  2016-10-01

3.  Health Benefits Mandates and Their Potential Impacts on Racial/Ethnic Group Disparities in Insurance Markets.

Authors:  Shana Alex Charles; Ninez Ponce; Dominique Ritley; Sylvia Guendelman; Jennifer Kempster; John Lewis; Joy Melnikow
Journal:  J Immigr Minor Health       Date:  2017-08

4.  Primary Care Physicians' Collection, Comfort, and Use of Race and Ethnicity in Clinical Practice in the United States.

Authors:  Vence L Bonham; Nkeiruka I Umeh; Brooke A Cunningham; Khadijah E Abdallah; Sherrill L Sellers; Lisa A Cooper
Journal:  Health Equity       Date:  2017-08-01
  4 in total

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