Skip Navigation U.S. Department of Health and Human Services www.hhs.gov
Agency for Healthcare Research Quality www.ahrq.gov
www.ahrq.gov

Differences in Access to Care for Asian and White Adults (Text Version)


Slide Presentation from the AHRQ 2008 Annual Conference


On September 8, 2008, Merrile Sing, Ph.D., made this presentation at the 2008 Annual Conference. Select to access the PowerPoint® presentation (705 KB).


Slide 1

Differences in Access to Care for Asian and White Adults

Merrile Sing, Ph.D.
September 8, 2008

Slide 2

Policy Context

  • Many Asians face significant linguistic and cultural barriers:
    • Approximately, 25% of Asians live in linguistically isolated households (Census 2000).
    • Approximately, 63% of Asians are immigrants (Census 2000).
  • Some Asian American subgroups are at greater risk than non-Hispanic Whites for certain diseases, such as diabetes, stomach and liver cancer, hepatitis B, and tuberculosis.

Slide 3

Research Objectives

  • To estimate adjusted differences in access to care between non-Hispanic White and Asian adults.
  • To identify factors that have the greatest marginal effects on improving access to care.

Slide 4

Previous Research

  • Moy et al. (2008). "Community Variation: Disparities in Health Care Quality Between Asian and White Medicare Beneficiaries."
  • Miltiades and Wu (2008). "Factors Affecting Physician Visits in Chinese and Chinese Immigrant Samples."
  • Snyder et al. (2000). "Access to Medical Care Reported by Asians and Pacific Islanders in a West Coast Physician Group Association"
  • AHRQ (2007), National Healthcare Disparities Report.

Slide 5

Study Design

  • Data are from the Medical Expenditure Panel Survey (MEPS) & Area Resource File, 2002-2005:
    • MEPS contains a nationally representative sample of households in the U.S. civilian, non-institutionalized population.
  • Sample includes non-Hispanic adults age 18 and older:
    • There are 3,779 Asians and 52,498 Whites.
  • Andersen typology of access to care is used.
  • Outcome variables are binary:
    • Usual source of care (excluding emergency room).
    • At least one office visit during past year.

Slide 6

Access to Care

Slide 7

Andersen Typology: Control Variables

Access depends on:

  • Predisposing characteristics.
  • Enabling Resources.
  • Illness level or perceived need.

Slide 8

Predisposing Characteristics

  • Demographic:
    • Age, sex, marital status.
  • Social structure:
    • Education.
    • Acculturation:
      • Difficulty speaking English.
      • In linguistically isolated family.
      • Immigrant <5 years in U.S.
      • Immigrant 5–14 years in U.S.
  • Attitudes:
    • Overcome illness without medical professional.
    • More willing to take risk.
    • Always uses seat belt.

Slide 9

Enabling Resources

  • Family:
    • Income.
    • Insurance coverage.
  • Community:
    • Urban-rural (using Metropolitan Statistical Areas).
    • Census Region (4).
    • Active non-federal MDs/1,000 population (county).
    • Number of Federally Qualified Health Centers (county).
    • Percent Asian population in county.

Slide 10

Illness/Perceived Need

  • Self-rated general health.
  • Poor mental health (Mental Component Summary).
  • Number of chronic conditions.

Slide 11

Methods

Slide 12

Estimation Methods

  • Unadjusted differences in means.
  • Adjusted differences (multivariate logistic regressions):
    • Marginal effects estimated by method of recycled predictions.
    • Standard errors estimated using balanced repeated replicates.

Slide 13

Marginal Effects on Access to Care

Which factors have the greatest marginal effects on improving access to care?

  • Predisposing conditions with and without acculturation variables.
  • Enabling resources.
  • Perceived need.
  • All control variables.

Slide 14

Unadjusted Differences

Slide 15

Access to Care Adults Age 18+

Screen shot of a bar graph showing:

Usual source of care:
White: 81% of the population
Asian: 70%** of the population

Office visit:
White: 78% of the population
Asian: 63%** of the population

Note: ** Significantly different from White at 0.05 (0.01) level or better.
Source: MEPS 2002-2005, Adults eligible for Access Supplement

Slide 16

Acculturation Immigrants

Screen shot of a bar graph showing:

  • <5 years in the U.S.:
    • White: 1% of the population.
    • Asian: 15%** of the population.
  • 5-14 years in the U.S.:
    • White: 1% of the population.
    • Asian: 28%** of the population.
  • 15+ years in the U.S.:
    • White: 3% of the population.
    • Asian: 40%** of the population.

Note: ** Significantly different from White at 0.05 (0.01) level or better.
Source: MEPS 2002-2005, Adults eligible for Access Supplement

Slide 17

Acculturation English Language

Screen shot of a bar graph showing:

  • Difficulty with English:
    • White: 0.4% of the population.
    • Asian: 12%** of the population.
  • Linguistically isolated family:
    • White: 0.2% of the population.
    • Asian: 5%** of the population.

Note: ** Significantly different from White at 0.05 (0.01) level or better.
Source: MEPS 2002-2005, Adults eligible for Access Supplement

Slide 18

Factors Associated with Access to Care

Slide 19

Variables associated with Usual Source of Care

  • Marginal effect:
    • Asian - 0.039* (0.019).
  • Enabling:
    • Income.
    • Insurance status.
    • MSA.
    • Census Region.
  • Perceived need:
    • Number of chronic conditions.
    • Self-rated health.
  • Predisposing:
    • Immigrant <5 years in the U.S.
    • Immigrant 5-14 years in the U.S.
    • Difficulty with English.
    • Asian* difficulty with English.
    • Family size, age, gender, marital status, and attitudes.

Note: Year 2004- Year 2005–
Source: MEPS 2002–2005.

Slide 20

Variables associated with Office Visit(s)

  • Marginal effect:
    • Asian - 0.077** (0.015).
  • Enabling:
    • Income.
    • Insurance status.
    • MSA.
    • Census Region.
    • Active MDs/1000 population.
  • Perceived need:
    • Number of chronic conditions.
    • Self-rated general health.
    • Self-rated mental health
  • Predisposing:
    • Immigrant <5 years in the U.S.
    • Difficulty with English.
    • Education.
    • Family size, age, gender, marital status, and attitudes.

Note: Year 2004+
Source: MEPS 2002–2005.

Slide 21

Estimated Marginal Effects

Slide 22

Marginal Effects on Access to Care

Unadjusted Usual Source of Care Office Visit(s)
White 0.811 (0.004) 0.784 (0.003)
Asian 0.701 (0.013) 0.630 (0.011)
Difference -0.110** -0.154**
Adjusted differences:
Marginal effects controlling for:
Usual Source of Care Office Visit(s)
Predisposing (w/o acculturation) -0.115** -0.143**
Predisposing (w/acculturation) -0.055** -0.102**
Enabling -0.078** -0.123**
Perceived need -0.068** -0.098**
All variables -0.039** -0.077**

Slide 23

Conclusions

Asian adults were less likely than Whites to have a usual source of care or an office visit, after controlling for predisposing and enabling characteristics and perceived need.

Greatest Marginal Effects on Access to Care

Care Type Predisposing with acculturation Enabling Perceived
Need
Usual Source of Care X    
Office Visit     X

Slide 24

Policy Relevance

Findings suggest areas to focus on for improving access to care for Asian adults:

  • Translating general medical information and Medicaid applications into Asian languages may improve access to care for some Asians.
  • Educating providers about differences in culture and disease incidence for Asians compared with non-Hispanic Whites.

Current as of January 2009


Internet Citation:

Differences in Access to Care for Asian and White Adults. Slide Presentation from the AHRQ 2008 Annual Conference (Text Version). January 2009. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/about/annualmtg08/090808slides/Sing.htm


 

AHRQ Advancing Excellence in Health Care