This article discusses the urgency of focusing on health disparities for the Asian American, Native Hawaiian, and Pacific Islander (AA and NHPI) communities and lays out three key policy priorities for the White House Initiative on Asian Americans, Native Hawaiians, and Pacific Islanders to advance health equity for the AA and NHPI communities: Anti-Asian hate and violence, data disaggregation, and language access.

Objective To examine individual‐ and community‐level factors associated with racial/ethnic differences in individuals’ opioid prescription use. Data Sources Outpatient opioid prescription utilization and demographic, socioeconomic, and health characteristics from a nationally representative sample of the US noninstitutionalized civilian population obtained from 2013‐2016 Medical Expenditure Panel Survey (MEPS) data and combined with 2012‐2016 American Community Survey data and 2015 Health Area Resources File data. Study Design We use the Oaxaca‐Blinder decomposition method to disaggregate racial/ethnic differences in prescription opioid utilization into differences explained by underlying predisposing, enabling and need characteristics, and unexplained differences. Data Collection/Extraction Methods We use restricted‐use geographic identifiers to supplement the MEPS data with information on community characteristics and local health care resources. Principal Findings The average annual rate of any outpatient opioid prescription use was higher for non‐Hispanic whites (15.8%; standard errors [SE]: 0.3) than for non‐Hispanic blacks and Hispanics by 1.4 percentage points (SE: 0.5) and 6.2 percentage points (SE: 0.4), respectively. The smaller difference between non‐Hispanic blacks and whites is not explained by the differences in the risk factors, while almost all the difference between Hispanics and non‐Hispanic whites can be explained by the differences in the means of the risk factors. The differences in the prevalence of pain, the rate of being United States‐born, and the racial/ethnic composition of the community explain 2.4 (SE: 0.2), 1.4 (SE: 0.3), and 1.9 (SE: 0.4) percentage‐point differences, respectively. Pain prevalence explains the difference regardless of opioid potency, while foreign‐born status and community racial/ethnic composition explain the difference in higher‐potency opioid utilization only. Conclusions This study underscores the importance of accounting for both individual and community characteristics when investigating patterns in opioid use. Our results could assist policy makers in tailoring strategies to promote safer and more effective pain management based on individual and community characteristics.

A large body of literature documents the importance of child support for children’s wellbeing, though little is known about the child support behaviors of mixed-status families, a large and rapidly growing population in the United States. In this paper, we use data from the Fragile Families and Child Wellbeing Study to investigate the impact of citizenship status on formal and informal child support transfers among a nationally representative sample of parents who have citizen children. Probit regression models and propensity score matching (PSM) estimators show that mixed-status families are significantly less likely to have child support orders and child support receipt compared to their citizen counterparts. We found that mothers’ knowledge of the child support system increases the probability of establishing paternity. However, cultural differences in knowledge of and perception about the U.S. child support system between mixed-status families and citizen families do not have an impact on the probability of getting a child support order, child support receipt, or in-kind child support. Rather, institutional factors such as collaborations between welfare agencies and child support enforcement agencies as well as state child support enforcement efforts have a significant impact on formal child support outcomes. The results are robust against different model specifications, measure constructions, and use of datasets. These findings have important policy implications for policy makers and researchers interested in reducing child poverty in complex family structures and underscore the need to revisit child support policies for mixed-status families.

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IntroductionThe safe, effective, and efficient use of pharmaceutical health services is a critical area of public health and social policy. Implementation and monitoring studies often use single data sources but require diverse data elements pertaining to patients and health services. Linking multiple data sources may enable more comprehensive studies. Objectives and ApproachThe objective of this presentation is to describe three applied pharmaceutical health services projects in the United States that use data linkage to support program monitoring. A conceptual model was defined including the following key domains: (1) contextual determinants; (2) pharmacy service availability and coverage by payers; (3) receipt/use of services by patients; and (4) outcomes such as clinical outcomes, patient satisfaction and healthcare costs. Applied studies were selected to illustrate data linkage across different domains. For each study, we present the data sources used and the domains addressed by each data source. We also describe the linkage process. ResultsStudy 1 assesses distance between patients and pharmacies in-network for health plans. It determined pharmacy address and patient ZIP code using several Medicare datasets and calculated driving distance using geocoding software. Study 2 measures if patients targeted for services receive an intervention designed to prevent adverse drug events and improve patient health outcomes while reducing healthcare costs. Targeted beneficiaries are determined using Medicare administrative data and delivery of services is assessed based on a custom-developed encounter data set, linked by beneficiary. Study 3 examines the association between prescription drug formulary design, medication use, and cost and health outcomes. For this, formulary data are obtained from a commercial source and utilization/outcomes data from commercial claims data. These datasets are linked by payer. Conclusion/ImplicationsMany data sources are available for pharmaceutical health services research studies and linkage can be made at the patient, region, or payer level to support program monitoring and evaluation. Data linkage enables the inclusion of multiple domains, although multiple linkages and/or custom data may be needed for more complex studies.