Online Program

Healthcare utilization varies by race/ethnicity among low-income Baltimore residents with the same insurance coverage

Wednesday, November 6, 2013 : 9:30 a.m. - 9:45 a.m.

Alicia Riley, MA MPH, Health Determinants & Disparities Practice, SRA International, Inc., Rockville, MD
African American and Hispanic/Latino patients experience disparities in health outcomes compared to non-Hispanic Whites. Data suggest that these disparities in outcomes may be partially explained by barriers to healthcare utilization, like insurance coverage. Several studies have shown that people who are uninsured and underinsured are less likely to seek healthcare than those with insurance, and that racial/ethnic minorities are more likely to be un/underinsured than Whites. Less is known, however, about variation in healthcare utilization by race/ethnicity among patients with the same insurance coverage. The Access Partnership (TAP) is an initiative of the Johns Hopkins network that guarantees coverage of primary and specialty care appointments to un/underinsured patients residing in one of seven target zip codes in Baltimore City and demonstrating financial need. No research has been done into variations by ethnicity among TAP patients. This study employed a cross-sectional design using secondary data extracted from an administrative database. It measured variation by race/ethnicity in counts of medical appointments among TAP enrolled patients of Johns Hopkins Hospital and Bayview Medical Center. Demographic and appointment data was extracted from DataMart. Participants included in the analysis were 817 low-income patients of the Johns Hopkins clinical network, residing in Baltimore City and enrolled in The Access Partnership insurance program between May 2009 and February 2012. Patients were excluded if we had difficulty finding a unique medical record, if they had no appointments billed to TAP, and if they had erroneous appointment counts. Poisson regression, controlling for days eligible for TAP coverage, was used to measure the effects of the covariates (race/ethnicity, sex, age, and zip code) on the outcome variables (number of appointments and total charges). Appointment rate was calculated using the continuous count of appointments over days with TAP insurance coverage. Multivariate statistical analysis, employing a quasi likelihood adjustment, showed significantly lower rates of appointments among African American and Hispanic/Latino patients than Non- Hispanic Whites. African American NH patients were only 0.58 times (95% CI: 0.45, 0.76) as likely as White patients to have an appointment and Hispanic patients were 0.38 times (95% CI: 0.28, 0.50) as likely as White patients to have an appointment. The results suggest that even among patients with equivalent insurance coverage for healthcare, racial/ethnic disparities persist in healthcare utilization as measured by appointment rate. Further research is warranted to understand how these trends are affected by time with expanded insurance coverage and type of medical visits.

Learning Areas:

Advocacy for health and health education
Chronic disease management and prevention
Diversity and culture
Planning of health education strategies, interventions, and programs
Public health or related research

Learning Objectives:
Describe one example of an innovative community health insurance program designed for low-income individuals without coverage for specialty care Analyze the factors that influence healthcare utilization and name at least two factors Discuss why equivalent insurance coverage may not be sufficient to predict healthcare utilization Reflect on the consequences that race/ethnicity's influence on the number of patient appointments may have on disparities in disease outcomes

Keyword(s): Health Care Utilization, Health Disparities

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I was the principal investigator on this study. I obtained the medical record data from Johns Hopkins Hospitals to conduct the analysis, designed the methods, and performed the statistical analysis using STATA. I worked closely with administrators of the health insurance model that granted coverage to the patients whose data was analyzed for this study. I have a Masters degree in Epidemiology and Biostatistics.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.