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The American Journal of Managed Care March 2019
Fragmented Ambulatory Care and Subsequent Emergency Department Visits and Hospital Admissions Among Medicaid Beneficiaries
Lisa M. Kern, MD, MPH; Joanna K. Seirup, MPH; Mangala Rajan, MBA; Rachel Jawahar, PhD, MPH; and Susan S. Stuard, MBA
Incorrect and Missing Author Initials in Affiliations and Authorship Information
From the Editorial Board: Austin Frakt, PhD
Austin Frakt, PhD
Implications of Eligibility Category Churn for Pediatric Payment in Medicaid
Deena J. Chisolm, PhD; Sean P. Gleeson, MD, MBA; Kelly J. Kelleher, MD, MPH; Marisa E. Domino, PhD; Emily Alexy, MPH; Wendy Yi Xu, PhD; and Paula H. Song, PhD
Factors Influencing Primary Care Providers’ Decisions to Accept New Medicaid Patients Under Michigan’s Medicaid Expansion
Renuka Tipirneni, MD, MSc; Edith C. Kieffer, PhD, MPH; John Z. Ayanian, MD, MPP; Eric G. Campbell, PhD; Cengiz Salman, MA; Sarah J. Clark, MPH; Tammy Chang, MD, MPH, MS; Adrianne N. Haggins, MD, MSc; Erica Solway, PhD, MPH, MSW; Matthias A. Kirch, MS; and Susan D. Goold, MD, MHSA, MA
Did Medicaid Expansion Matter in States With Generous Medicaid?
Alina Denham, MS; and Peter J. Veazie, PhD
Access to Primary and Dental Care Among Adults Newly Enrolled in Medicaid
Krisda H. Chaiyachati, MD, MPH, MSHP; Jeffrey K. Hom, MD, MSHP; Charlene Wong, MD, MSHP; Kamyar Nasseh, PhD; Xinwei Chen, MS; Ashley Beggin, BS; Elisa Zygmunt, MSW; Marko Vujicic, PhD; and David Grande, MD, MPA
Medicare Annual Wellness Visit Association With Healthcare Quality and Costs
Adam L. Beckman, BS; Adan Z. Becerra, PhD; Anna Marcus, BS; C. Annette DuBard, MD, MPH; Kimberly Lynch, MPH; Emily Maxson, MD; Farzad Mostashari, MD, ScM; and Jennifer King, PhD
Common Elements in Opioid Use Disorder Guidelines for Buprenorphine Prescribing
Timothy J. Atkinson, PharmD, BCPS, CPE; Andrew J.B. Pisansky, MD, MS; Katie L. Miller, PharmD, BCPS; and R. Jason Yong, MD, MBA
Specialty Care Access for Medicaid Enrollees in Expansion States
Justin W. Timbie, PhD; Ashley M. Kranz, PhD; Ammarah Mahmud, MPH; and Cheryl L. Damberg, PhD
Gender Differences in Prescribing of Zolpidem in the Veterans Health Administration
Guneet K. Jasuja, PhD; Joel I. Reisman, AB; Renda Soylemez Wiener, MD, MPH; Melissa L. Christopher, PharmD; and Adam J. Rose, MD, MSc
Cost Differential of Immuno-Oncology Therapy Delivered at Community Versus Hospital Clinics
Lucio Gordan, MD; Marlo Blazer, PharmD, BCOP; Vishal Saundankar, MS; Denise Kazzaz; Susan Weidner, MS; and Michael Eaddy, PharmD, PhD
Currently Reading
Health Insurance Literacy: Disparities by Race, Ethnicity, and Language Preference
Victor G. Villagra, MD; Bhumika Bhuva, MA; Emil Coman, PhD; Denise O. Smith, MBA; and Judith Fifield, PhD

Health Insurance Literacy: Disparities by Race, Ethnicity, and Language Preference

Victor G. Villagra, MD; Bhumika Bhuva, MA; Emil Coman, PhD; Denise O. Smith, MBA; and Judith Fifield, PhD
Racial/ethnic minorities are disproportionately at risk for adverse health and financial consequences due to lower health insurance literacy compared with white enrollees.
ABSTRACT

Objectives: To measure Connecticut’s Affordable Care Act qualified health plan enrollees’ health insurance literacy (HIL) by race, ethnicity, and language preference. 

Study Design: Statewide landline and cell phone telephonic survey.

Methods: Geographically balanced cohort that oversampled black and Hispanic enrollees. Questions tested enrollees’ knowledge of basic health insurance terminology and their use. Survey data were supplemented by deidentified administrative data from the state’s health insurance exchange.

Results: Overall, subjects answered 62% of 13 questions correctly. The percentages of correct answers were 53% for black enrollees, 50% for Hispanic enrollees, 74% for white enrollees, and 45% for Spanish-speaking enrollees. The differences by race, ethnicity, and language preference were statistically significant. Overall, enrollees with a college education scored higher across all demographic groups, but disparities by race and ethnicity persisted.

Conclusions: Health insurance terminology and use rules confuse consumers, especially racial and ethnic minorities. Differences in HIL may be a previously underrecognized source of healthcare disparities because even minor errors can result in delayed care or unanticipated medical bills. Low HIL can diminish the practical value of health insurance and exacerbate perceptions of health insurance as offering insufficient value for premium price. Additional research on ways to improve HIL and investments in insurance navigation support for black and Hispanic enrollees are needed.

Am J Manag Care. 2019;25(3):e71-e75
Takeaway Points

Consumers can derive disparate value from identical plans based on their health insurance literacy (HIL). Our study measured HIL among qualified health plans’ enrollees. Although gaps in HIL were evident among all enrollees, racial/ethnic minorities had significantly lower HIL than white enrollees. Low HIL coupled with complex health plan rules present a barrier to care and put minorities at constant risk for unpredictable financial liabilities.

Three corrective measures are needed to enhance the value of insurance for all:
  • Palliative, short-term measures: research in HIL education, especially for minorities, and enhanced point-of-care insurance coaching and support.
  • Systemic, long-term measure: health insurance simplification.
With the implementation of health insurance exchanges established by the Affordable Care Act (ACA), more than 20 million Americans gained access to health insurance. Of those, about 10 million enrolled in private insurance plans called qualified health plans (QHPs) that met certain ACA requirements—37% for the first time.1 In doing so, the newly insured entered a complex system of jargon, rules, limits, exceptions, and exclusions. Policy makers understood from the outset that health insurance literacy (HIL) would be a key factor in the long-term success of the ACA. In 2011, an HIL roundtable coined the following working definition: HIL “measures the degree to which individuals have the knowledge, ability, and confidence to find and evaluate information about health plans, select the best plan for their own (or their family’s) financial and health circumstances, and use the plan once enrolled.”2

To be of practical value, HIL requires consumers to have basic health and financial literacy and basic numeracy skills to calculate out-of-pocket expenses, decide whether they can afford to act, and know when they have been incorrectly billed, for instance. For this reason, HIL must be viewed as a unique skill, without which consumers cannot rationally choose or use health insurance or realize the full value of their policies. Several national studies have shown that consumers, even highly educated ones, have difficulty choosing and using their health insurance2-4 and that HIL levels vary widely across population groups. Racial and ethnic minorities, young adults, and those with limited English language proficiency are especially disadvantaged.5 Poor HIL is compounded by insurance product complexity.6,7 These conditions can widen existing disparities in health and well-being among minorities.

In 2013, Connecticut launched its health insurance exchange, Access Health Connecticut (AHCT). An extensive statewide consumer outreach campaign resulted in a significant reduction in the state’s uninsured rate by 2015.8 For 2 consecutive years after the first open enrollment period, AHCT surveys revealed that compared with 34% of white enrollees, 40% of black and 44% of Hispanic enrollees in QHPs had not used their insurance; additionally, compared with 19% of white enrollees, 46% of black enrollees and 52% of Hispanic enrollees did not have a primary care provider. These statistics prompted a need to measure enrollees’ HIL, a potential contributing cause of disparate utilization. This paper presents the results of the first study of HIL among QHP enrollees by race, ethnicity, and language preference in Connecticut.

METHODS

The telephonic survey target was 500 enrollees stratified by county and race/ethnicity. The sample was extracted from a pool of more than 66,000 insured AHCT QHP enrollees inclusive of the 2013, 2014, and 2015 enrollment periods. Based on results of previous national studies that showed lower HIL among racial/ethnic minorities, the survey oversampled black and Hispanic enrollees. Oversampling was defined as a preponderance of people of color compared with the frequency in the general population using the 2010 Connecticut Census as a reference. Therefore, the stratified sample target was 50% white, 25% black, and 25% Hispanic (vs 70%, 10%, and 14%, respectively, in Census) from Connecticut’s 8 counties.

The survey was conducted by an independent third-party vendor by random selection from the sample pool until the stratified targets were met. Telephone outreach included landline and cell phone numbers. Interviews were conducted in English or Spanish based on enrollee preference. Participants were offered a $5 gift card for their participation. The survey was fielded from July 13, 2016, to July 29, 2016.
The 25-minute survey included 13 questions about knowledge and use of health insurance terminology. Responses were augmented with additional administrative data by AHCT. A fully deidentified data set was used for statistical analysis.

Analysis consisted of descriptive statistics, the χ2 test for categorical or ordinal variables, independent samples t tests for 2-group comparisons, univariate analysis of variance for more than 2 groups, and linear regressions for continuous outcomes, with and without categorical copredictors. Analyses were done in Stata 15 (StataCorp, LLC; College Station, Texas), and statistical significance for all tests was established at P <.05.

The study was exempted by the University of Connecticut Institutional Review Board because only deidentified data were used in the analysis.


 
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