Islander Beneficiaries Research Articles

Decomposition analysis of racial and ethnic differences in receipt of immediate postpartum, long-acting, reversible, and permanent contraception

ObjectivesThis study aimed to determine the factors contributing to racial and ethnic disparities in the use of immediate postpartum, long-acting reversible contraception (IPP LARC) and permanent contraception among Medicaid recipients. Study designWe conducted a cross-sectional study using 3 years of national Medicaid claims data to examine the rates of IPP LARC use alone and a composite measure of postpartum permanent contraception and IPP LARC within 7 days of delivery by race and ethnicity. We used a Blinder–Oaxaca model to quantify the extent to which medical complexity, age, rurality, mode of delivery, and year explained differences in outcomes among different minoritized groups in comparison to non-Hispanic White women. ResultsOur study sample contained 1,729,663 deliveries occurring from 2016 through 2018 among 1,605,199 people living in 16 states. IPP LARC use rates were highest among Black (2.2%), followed by American Indian and Alaska Native at 2.1% and Hawaiian/Pacific Islander beneficiaries at 1.9%, Hispanic (all races) at 1.2%, and Asian at 1.0%. IPP LARC was lowest among White beneficiaries (0.8%). Medical complexity, age, rurality, year, and mode of delivery explained only 12.3% of the difference in IPP LARC rates between Black and White beneficiaries. Postpartum permanent contraception was highest among White (7.6%), Hispanic (7.2%), and American Indian and Alaska Native (6.8%), followed by Black (6.3%), Hawaiian/Pacific Islander (5.1%) and lowest among Asian women (4.1%). When we examined the use of IPP LARC or postpartum permanent contraception together, these same factors explained 94.4% of the differences between Black and White beneficiaries. ConclusionsWhile differences in the use of IPP LARC by race and ethnicity were identified, our findings suggest that overall use of inpatient highly effective contraception are similar across racial and ethnic groups. ImplicationsWhen IPP LARC and postpartum permanent contraception are examined jointly, their use is similar across racial and ethnic groups.

Racial and Ethnic Disparities in Opioid Prescribing on Hospital Discharge Among Older Adults: A National Retrospective Cohort Study.

Disparities in opioid prescribing among racial and ethnic groups have been observed in outpatient and emergency department settings, but it is unknown whether similar disparities exist at discharge among hospitalized older adults. To determine filled opioid prescription rates on hospital discharge by race/ethnicity among Medicare beneficiaries. Retrospective cohort study. Medicare beneficiaries 65 years or older discharged from hospital in 2016, without opioid fills in the 90 days prior to hospitalization (opioid-naïve). Race/ethnicity was categorized by the Research Triangle Institute (RTI), grouped as Asian/Pacific Islander, Black, Hispanic, other (American Indian/Alaska Native/unknown/other), and White. The primary outcome was an opioid prescription claim within 2 days of hospital discharge. The secondary outcome was total morphine milligram equivalents (MMEs) among adults with a filled opioid prescription. Among 316,039 previously opioid-naïve beneficiaries (mean age, 76.8 years; 56.2% female), 49,131 (15.5%) filled an opioid prescription within 2 days of hospital discharge. After adjustment, Black beneficiaries were 6% less likely (relative risk [RR] 0.94, 95% CI 0.91-0.97) and Asian/Pacific Islander beneficiaries were 9% more likely (RR 1.09, 95% CI 1.03-1.14) to have filled an opioid prescription when compared to White beneficiaries. Among beneficiaries with a filled opioid prescription, mean total MMEs were lower among Black (356.9; adjusted difference - 4%, 95% CI - 7 to - 1%), Hispanic (327.0; adjusted difference - 7%, 95% CI - 10 to - 4%), and Asian/Pacific Islander (328.2; adjusted difference - 8%, 95% CI - 12 to - 4%) beneficiaries when compared to White beneficiaries (409.7). Black older adults were less likely to fill a new opioid prescription after hospital discharge when compared to White older adults and received lower total MMEs. The factors contributing to these differential prescribing patterns should be investigated further.

332-OR: Medicare Part B Fee-for-Service Claims for Diabetes-Related Eye Diseases

Background: Diabetic retinopathy is the leading cause of incident blindness among working age U.S. adults. Only slightly more than half of Medicare beneficiaries with diabetes receive an annual eye exam, and this rate is lower among Hispanic and black beneficiaries compared to white beneficiaries. Objective: We examine racial/ethnic differences in diabetes-related eye disease and treatment claims, among Medicare beneficiaries with diabetes. Methods: We analyzed 2017 Medicare claims for 8,341,000 beneficiaries (both ≥65 years and <65 years with disabilities) with diagnosed diabetes who were continuously enrolled during 2017 in Part B fee-for-service (FFS) insurance. Diagnoses for diabetes and diabetes-related eye diseases were defined using ICD-10-CM diagnosis codes and treatments were classified using procedure codes in the claims. We present crude national percentages. Results: In 2017, 28% of FFS beneficiaries had diabetes. Of these, 9.6% had a claim for any diabetes-related eye disease; this annual rate was higher among Hispanic (13.1%), non-Hispanic black (11.2%), and Asian/Pacific Islander (11.4%) beneficiaries than among white beneficiaries (8.7%). Early/mild diabetic retinopathy was the most prevalent form (6.3%) and diabetic macular edema was the least prevalent (0.6%). Of beneficiaries with diabetes-related eye disease, 15.2% had at least one type of treatment; treatment types received were anti-vascular endothelial growth factor injections (11.8%), laser photocoagulation (4.7%), vitrectomy (1.3%), and retinal detachment repair (0.7%). Annual prevalence of any treatment was higher among Hispanic (19.0%) and non-Hispanic black (15.5%) beneficiaries compared to white beneficiaries (14.7%); it was lowest among Asian/Pacific Islander beneficiaries (12.9%). Conclusions: Annually, around one-in-ten Medicare Part B FFS beneficiaries with diabetes has a claim for diabetes-related eye disease, and this rate is higher among Hispanic and black beneficiaries. Disclosure E.A. Lundeen: None. D.B. Rein: None. J. Wittenborn: None. J.B. Saaddine: None.

Examining Race and Ethnicity Information in Medicare Administrative Data.

Racial and ethnic disparities are observed in the health status and health outcomes of Medicare beneficiaries. Reducing these disparities is a national priority, and having high-quality data on individuals' race and ethnicity is critical for researchers working to do so. However, using Medicare data to identify race and ethnicity is not straightforward. Currently, Medicare largely relies on Social Security Administration data for information about Medicare beneficiary race and ethnicity. Directly self-reported race and ethnicity information is collected for subsets of Medicare beneficiaries but is not explicitly collected for the purpose of populating race/ethnicity information in the Medicare administrative record. As a consequence of historical data collection practices, the quality of Medicare's administrative data on race and ethnicity varies substantially by racial/ethnic group; the data are generally much more accurate for whites and blacks than for other racial/ethnic groups. Identification of Hispanic and Asian/Pacific Islander beneficiaries has improved through use of an imputation algorithm recently applied to the Medicare administrative database. To improve the accuracy of race/ethnicity data for Medicare beneficiaries, researchers have developed techniques such as geocoding and surname analysis that indirectly assign Medicare beneficiary race and ethnicity. However, these techniques are relatively new and data may not be widely available. Understanding the strengths and limitations of different approaches to identifying race and ethnicity will help researchers choose the best method for their particular purpose, and help policymakers interpret studies using these measures.