Literature DB >> 26487321

Using Bayesian Imputation to Assess Racial and Ethnic Disparities in Pediatric Performance Measures.

David P Brown1, Caprice Knapp2, Kimberly Baker3, Meggen Kaufmann3.   

Abstract

OBJECTIVE: To analyze health care disparities in pediatric quality of care measures and determine the impact of data imputation. DATA SOURCES: Five HEDIS measures are calculated based on 2012 administrative data for 145,652 children in two public insurance programs in Florida.
METHODS: The Bayesian Improved Surname and Geocoding (BISG) imputation method is used to impute missing race and ethnicity data for 42 percent of the sample (61,954 children). Models are estimated with and without the imputed race and ethnicity data. PRINCIPAL
FINDINGS: Dropping individuals with missing race and ethnicity data biases quality of care measures for minorities downward relative to nonminority children for several measures.
CONCLUSIONS: These results provide further support for the importance of appropriately accounting for missing race and ethnicity data through imputation methods. © Health Research and Educational Trust.

Entities:  

Keywords:  Bayesian imputation; HEDIS; Medicaid; children; disparities; racial/ethnic differences

Mesh：

Year:  2015        PMID： 26487321      PMCID： PMC4874818          DOI： 10.1111/1475-6773.12405

Source DB:  PubMed          Journal:  Health Serv Res        ISSN： 0017-9124            Impact factor:   3.402


  10 in total

1.  Primary care experience and racial disparities in self-reported health status.

Authors:  Leiyu Shi; Lisa H Green; Sophia Kazakova
Journal:  J Am Board Fam Pract       Date:  2004 Nov-Dec

2.  Use of geocoding in managed care settings to identify quality disparities.

Authors:  Allen M Fremont; Arlene Bierman; Steve L Wickstrom; Chloe E Bird; Mona Shah; José J Escarce; Thomas Horstman; Thomas Rector
Journal:  Health Aff (Millwood)       Date:  2005 Mar-Apr       Impact factor: 6.301

3.  Collecting adequate data on racial and ethnic disparities in health: the challenges continue.

Authors:  Linda T Bilheimer; Jane E Sisk
Journal:  Health Aff (Millwood)       Date:  2008 Mar-Apr       Impact factor: 6.301

4.  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

5.  Power of tests for a dichotomous independent variable measured with error.

Authors:  Daniel F McCaffrey; Marc N Elliott
Journal:  Health Serv Res       Date:  2008-06       Impact factor: 3.402

6.  A new method for estimating race/ethnicity and associated disparities where administrative records lack self-reported race/ethnicity.

Authors:  Marc N Elliott; Allen Fremont; Peter A Morrison; Philip Pantoja; Nicole Lurie
Journal:  Health Serv Res       Date:  2008-05-12       Impact factor: 3.402

Review 7.  Use of geocoding and surname analysis to estimate race and ethnicity.

Authors:  Kevin Fiscella; Allen M Fremont
Journal:  Health Serv Res       Date:  2006-08       Impact factor: 3.402

8.  Child and adolescent health care quality and disparities: are we making progress?

Authors:  Denise Dougherty; Xiuhua Chen; Darryl T Gray; Alan E Simon
Journal:  Acad Pediatr       Date:  2014 Mar-Apr       Impact factor: 3.107

9.  Annual report on health care for children and youth in the United States: racial/ethnic and socioeconomic disparities in children's health care quality.

Authors:  Terceira Berdahl; Pamela L Owens; Denise Dougherty; Marie C McCormick; Yuriy Pylypchuk; Lisa A Simpson
Journal:  Acad Pediatr       Date:  2010 Mar-Apr       Impact factor: 3.107

10.  Profile of medical charges for children by health status group and severity level in a Washington State Health Plan.

Authors:  John M Neff; Virginia L Sharp; John Muldoon; Jeff Graham; Kristin Myers
Journal:  Health Serv Res       Date:  2004-02       Impact factor: 3.402
  10 in total
  2 in total

1.  Imputation of race/ethnicity to enable measurement of HEDIS performance by race/ethnicity.

Authors:  Ann Haas; Marc N Elliott; Jacob W Dembosky; John L Adams; Shondelle M Wilson-Frederick; Joshua S Mallett; Sarah Gaillot; Samuel C Haffer; Amelia M Haviland
Journal:  Health Serv Res       Date:  2018-12-03       Impact factor: 3.402

2.  The quality of social determinants data in the electronic health record: a systematic review.

Authors:  Lily A Cook; Jonathan Sachs; Nicole G Weiskopf
Journal:  J Am Med Inform Assoc       Date:  2021-12-28       Impact factor: 4.497
  2 in total

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