Clinical and public policy interventions to address food insecurity among children

PURPOSE OF REVIEW: This article describes the impacts of food insecurity (FI) on child health, outlines clinical and public policy interventions to mitigate FI in children, and defines new paradigms in population health to ameliorate the harmful effects of FI in children. RECENT FINDINGS: Rates of FI among children have dramatically increased with the onset of the COVID-19 pandemic, with particular adverse impact on low-income children. Population health innovations in screening, referral, and social service integration offer new opportunities to address FI. SUMMARY: Despite advances in clinical practice and public policy, FI remains a persistent issue for many US children. Clinicians and policymakers have opportunities to leverage clinical and community-based integration to improve service delivery opportunities to ameliorate childhood hunger and racial and socioeconomic inequity in the United States

Changes in Health Care-Related Financial Burden for US Families With Children Associated With the Affordable Care Act.

ImportanceThe Affordable Care Act (ACA) sought to improve access and affordability of health insurance. Although most ACA policies targeted childless adults, the extent to which these policies also impacted families with children remains unclear.ObjectiveTo examine changes in health care-related financial burden for US families with children before and after the ACA was implemented based on income eligibility for ACA policies.Design, setting, and participantsData used for this cohort study were obtained from the 2000-2017 Medical Expenditure Panel Survey, a nationally representative, population-based survey. Multivariable regression with a difference-in-differences estimator was used to examine changes in family financial burden before and after ACA implementation according to income-based ACA eligibility groups (≤138% [lowest-income], 139%-250% [low-income], 251%-400% [middle-income], and >400% [high-income] federal poverty level). The cohort included 92 165 families with 1 or more children (age ≤18 years) and 1 or more adult parents/guardians.ExposuresIncome-based eligibility groups during post-ACA years (calendar years 2014-2017) vs pre-ACA years (calendar years 2000-2013).Main outcomes and measuresFamily annual out-of-pocket (OOP) health care and premium cost burden relative to income. High OOP burden was determined based on a previously validated algorithm with relative cost thresholds that vary across incomes, and extreme OOP burden was defined as costs exceeding 10% of income. Premiums exceeding 9.5% of income were classified as burdensome and premiums relative to median household income defined an unaffordability index.ResultsCompared with high-income families who experienced a lesser change post-ACA implementation (high OOP burden, 1.1% pre-ACA vs 0.9% post-ACA), the lowest-income families saw the greatest reduction in high OOP burden (35.6% pre-ACA vs 23.7% post-ACA; difference-in-differences: -11.4%; 95% CI, -13.2% to -9.5%) followed by low-income families (24.6% pre-ACA vs 17.3% post-ACA, difference-in-differences: -6.8%; 95% CI, -8.7% to -4.9%) and middle-income families (6.1% pre-ACA vs 4.6% post-ACA, difference-in-differences: -1.2%; 95% CI, -2.3% to -0.01%). Although premiums rose for all groups, premium unaffordability was the least exacerbated for the lowest-, low-, and middle-income families compared with higher-income families.Conclusions and relevanceThe findings of this study suggest that low- and middle-income families with children who were eligible for ACA Medicaid expansions and Marketplace subsidies experienced greater reductions in health care-related financial burden after the ACA was implemented compared with families with higher incomes. However, despite ACA policies, many low- and middle-income families with children appear to continue to face considerable financial burden from premiums and OOP costs

Racial and Ethnic Differences in Managed Care Enrollment Among US Children

This survey study uses data from the 2018 Medical Expenditure Panel Survey Household Component to compare rates of health maintenance organization (HMO) enrollment, by race and ethnicity, for children with commercial and public coverage

“Pick a Plan and Roll the Dice”: A qualitative study of consumer experiences selecting a health plan in the non-group market

Background: For consumers without access to employer-sponsored or public insurance, health plan choices in the non-group (individual) insurance market that do not meet consumer needs have the potential for negative downstream implications for health and financial well-being. Objective: This qualitative interview study sought to understand consumers’ experiences and challenges with choosing a non-group health plan, among those who later had negative experiences with the plan they chose. Methods: We conducted semi-structured telephone interviews with a purposive sample of 36 participants from a large regional health insurance carrier in three states who enrolled in non-group plans in 2017 (21 in Affordable Care Act (ACA) Marketplace plans and 15 enrolled off-Marketplace). Participants were included if they reported negative experiences using their plan after enrollment, such as higher-than-expected medical costs. Interviews explored challenges choosing a plan; information needed for choosing; usefulness of available tools; and preferred format for interventions to improve plan choice experiences. We analyzed interview transcripts using thematic content analysis. Results: Study participants reported experiencing substantial challenges to choosing an insurance plan. Key barriers included understanding insurance terms, finding relevant information, and making comparisons across plans. Participants valued the ability to make comparisons across carriers when using the Marketplace websites but were less satisfied with customer service. Suggestions for improvement included greater standardization of plans and language and availability of customized one-on-one assistance. Conclusion: Findings from this study suggest that health plan selection in the non-group market presents challenges to consumers that may be addressed through enrollment assistance and improved presentation of information. Personalized assistance to find and choose coverage may lead to plan choices that better meet consumer needs and increase confidence choosing a plan in subsequent enrollment periods

Analysis of Racial and Ethnic Diversity of Population Served and Imaging Used in US Children\u27s Hospital Emergency Departments

Importance: Lower rates of diagnostic imaging have been observed among Black children compared with White children in pediatric emergency departments. Although the racial composition of the pediatric population served by each hospital differs, it is unclear whether this is associated with overall imaging rates at the hospital level, and in particular how it may be associated with the difference in imaging rates between Black and White children at a given hospital. Objective: To examine the association between the diversity of the pediatric population seen at each pediatric ED and variation in diagnostic imaging. Design, Setting, and Participants: Cross-sectional analysis of ED visits by patients younger than 18 years at 38 children\u27s hospitals from January 1, 2016, through December 31, 2019, using data from the Pediatric Health Information System. Data were analyzed from April to September 2021. Exposures: Proportion of patients from minoritized groups cared for at each hospital. Main Outcomes and Measures: The primary outcome was receipt of an imaging test defined as radiography, ultrasonography, computed tomography, or magnetic resonance imaging; adjusted odds ratios (aORs) were calculated to measure differences in imaging by race and ethnicity by hospital, and the correlation between the proportion of patients from minoritized groups cared for at each hospital and the aOR for receipt of diagnostic imaging by race and ethnicity was examined. Results: There were 12 310 344 ED visits (3 477 674 [28.3%] among Hispanic patients; 3 212 915 [26.1%] among non-Hispanic Black patients; 4 415 747 [35.9%] among non-Hispanic White patients; 6 487 660 [52.7%] among female patients) by 5 883 664 pediatric patients (mean [SD] age, 5.84 [5.23] years) to the 38 hospitals during the study period, of which 3 527 866 visits (28.7%) involved at least 1 diagnostic imaging test. Diagnostic imaging was performed in 1 508 382 visits (34.2%) for non-Hispanic White children, 790 961 (24.6%) for non-Hispanic Black children, and 907 222 (26.1%) for Hispanic children (P \u3c .001). Non-Hispanic Black patients were consistently less likely to receive diagnostic imaging than non-Hispanic White patients at each hospital, and for all imaging modalities. There was a significant correlation between the proportion of patients from minoritized groups cared for at the hospital and greater imaging difference between non-Hispanic White and non-Hispanic Black patients (correlation coefficient, -0.37; 95% CI, -0.62 to -0.07; P = .02). Conclusions and Relevance: In this cross-sectional study, hospitals with a higher percentage of pediatric patients from minoritized groups had larger differences in imaging between non-Hispanic Black and non-Hispanic White patients, with non-Hispanic White patients consistently more likely to receive diagnostic imaging. These findings emphasize the urgent need for interventions at the hospital level to improve equity in imaging in pediatric emergency medicine

Racial and Ethnic Differences in Insurer Classification of Nonemergent Pediatric Emergency Department Visits

IMPORTANCE: Government and commercial health insurers have recently enacted policies to discourage nonemergent emergency department (ED) visits by reducing or denying claims for such visits using retrospective claims algorithms. Low-income Black and Hispanic pediatric patients often experience worse access to primary care services necessary for preventing some ED visits, raising concerns about the uneven impact of these policies. OBJECTIVE: To estimate potential racial and ethnic disparities in outcomes of Medicaid policies for reducing ED professional reimbursement based on a retrospective diagnosis-based claims algorithm. DESIGN, SETTING, AND PARTICIPANTS: This simulation study used a retrospective cohort of pediatric ED visits (aged 0-18 years) for Medicaid-insured children and adolescents appearing in the Market Scan Medicaid database between January 1, 2016, and December 31, 2019. Visits missing date of birth, race and ethnicity, professional claims data, and Current Procedural Terminology codes of billing level of complexity were excluded, as were visits that result in admission. Data were analyzed from October 2021 to June 2022. MAIN OUTCOMES AND MEASURES: Proportion of ED visits algorithmically classified as nonemergent and simulated per-visit professional reimbursement after applying a current reimbursement reduction policy for potentially nonemergent ED visits. Rates were calculated overall and compared by race and ethnicity. RESULTS: The sample included 8 471 386 unique ED visits (43.0% by patients aged 4-12 years; 39.6% Black, 7.7% Hispanic, and 48.7% White), of which 47.7% were algorithmically identified as potentially nonemergent and subject to reimbursement reduction, resulting in a 37% reduction in ED professional reimbursement across the study cohort. More visits by Black (50.3%) and Hispanic (49.0%) children were algorithmically identified as nonemergent when compared with visits by White children (45.3%; P \u3c .001). Modeling the impact of the reimbursement reductions across the cohort resulted in expected per-visit reimbursement that was 6% lower for visits by Black children and 3% lower for visits by Hispanic children relative to visits by White children. CONCLUSIONS AND RELEVANCE: In this simulation study of over 8 million unique ED visits, algorithmic approaches for classifying pediatric ED visits that used diagnosis codes identified proportionately more visits by Black and Hispanic children as nonemergent. Insurers applying financial adjustments based on these algorithmic outputs risk creating uneven reimbursement policies across racial and ethnic groups