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OBJECTIVE: To estimate differences in scheduled and completed specialty referrals by race, ethnicity, language for care, and insurance type. STUDY DESIGN: We studied a retrospective cohort of 38 334 specialty referrals to a large children's hospital between March 2019 and March 2021. We included referrals for patients with primary care clinics within 5 miles of the hospital. We examined whether the odds of and time to scheduled and completed referrals differed by patient sociodemographic characteristics. RESULTS: Of all referrals, 62% were scheduled and 54% were completed. Referral completion rates were lower for patients with Black race (45%), Native Hawaiian/Pacific Islander race (48%), Spanish language (49%), and public insurance (47%). Odds of scheduled and completed referral were lower for Asian (aOR scheduled: 0.94, [95% CI: 0.89, 0.99]; aOR completed: 0.92 [0.87, 0.97]), Black (aOR scheduled: 0.86 [0.79, 0.94]; aOR completed: 0.80 [0.73, 0.87]), and publicly insured patients (aOR scheduled: 0.71 [0.66, 0.75]; aOR completed: 0.70 [0.66, 0.75]). Time to scheduled and completed referral was longer for Black (adjusted hazard ratio [aHR] scheduled: 0.93 [0.88, 0.98]; aHR completed: 0.93 [0.87, 0.99]) and publicly insured patients (aHR scheduled: 0.85 [0.82, 0.88]; aHR completed: 0.84 [0.80, 0.87]) and families with a language other than English (aHR scheduled: 0.66 [0.62, 0.70]; aHR completed: 0.92 [0.86, 0.99]). CONCLUSIONS: Within a geographically homogenous pediatric population, the odds and time to scheduled and completed specialty referrals differed by sociodemographic characteristics, suggesting the effects of discrimination. To improve access equity, health care organizations need clear and consistent referral workflows and more comprehensive metrics for access.

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Abstract How do governments distribute resources across economic sectors during a crisis? And why do some sectors receive more than others? The recent COVID-19 pandemic has highlighted the urgency of these questions. In this paper, we explore the extent to which a political economy perspective can help explain the characteristics of sector-specific state aid in the Netherlands, a traditionally corporatist country. While KLM, the biggest player in the Dutch aviation sector, was promised loans worth €3.4 billion, the horeca (hospitality) sector was denied a similar deal. Limited cross-case analysis eliminates purely economic accounts. We employed process-tracing and analyzed hundreds of national media articles to understand the influence of elected leaders, interest groups, and experts. We find that, against the backdrop of economic concerns, vote-seeking behavior by elected leaders as well as the strength and organization of interest groups influenced how much each sector could expect. Meanwhile, policy-seeking behavior helps explain the form that aid took. Our findings highlight the need to consider fiscal support in political economy terms, even during crises, and to explore the composition of state aid, not just its presence or amount.

Resumo Como são distribuídos os recursos de auxílio governamental entre os vários setores econômicos durante uma crise? E por que alguns sectores recebem mais do que outros? A recente pandemia da COVID-19 sublinhou a urgência destas questões. Neste artigo, discutimos como uma perspectiva de economia política pode ajudar a explicar as caraterísticas do auxílio estatal setorial nos Países Baixos, uma nação tradicionalmente corporativista. Enquanto o governo prometeu à KLM, o maior ator no setor da aviação holandês, empréstimos no valor de 3,4 mil milhões de euros, o horeca (sector da hotelaria) não recebeu um pacote de auxílio semelhante. A análise de casos elimina explicações puramente técnicas para esse fenômeno. Utilizamos process-tracing e fizemos uma análise de centenas de artigos publicados na mídia do país para compreender a influência dos líderes políticos, lobbies e peritos. Descobrimos que, num contexto de crise econômica, o comportamento eleitoreiro dos líderes políticos e a força e organização dos lobbies, determinaram a quantia que cada setor poderia esperar receber. Entretanto, os interesses no campo das políticas públicas ajudam a explicar a forma específica do auzílio. Nossas conclusões sublinham a necessidade de considerar o apoio fiscal em termos de economia política, mesmo durante crises, e de explorar não somente a existência ou o montante dos auxílios oferecidos pelo estado, mas também sua composição.

Resumen ¿Cómo se distribuyen los recursos de ayuda gubernamental entre los diferentes sectores económicos durante una crisis? ¿Y por qué algunos sectores reciben más que otros? La reciente pandemia de COVID-19 puso de relieve la importancia de estas cuestiones. En este artículo, exploramos cómo una perspectiva de economía política puede ayudar a entender la distribución del apoyo estatal en diferentes sectores en los Países Bajos, un país de tradición corporativista. Mientras que a KLM ‒el actor más importante del sector de aviación holandés‒ el gobierno le prometió préstamos de alrededor de 3.400 millones de euros, al sector HORECA (que congrega hoteles, restaurantes y cafeterías) se le denegó una ayuda similar. A través de un análisis cruzado de casos eliminamos razones puramente técnicas para este fenómeno. A continuación, utilizamos la metodología process-tracing y analizamos cientos de artículos de medios de comunicación holandeses para entender la influencia de líderes políticos, lobbies y expertos. Descubrimos que, en un contexto de crisis económica, el comportamiento electorero de los líderes políticos y el poder y organización de los lobbies determinaron la suma que cada sector podría esperar. Por otro lado, la estructura de dichas ayudas se explica a través del alineamiento político de los decisores políticos. Nuestros resultados subrayan la necesidad de estudiar el apoyo gubernamental en términos de economía política, inclusive durante crisis, y de explorar no solo la existencia o la cuantía de dichas ayudas sino también su composición.

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OBJECTIVE: To evaluate the effect of a standardized feeding approach using a clinical nutrition pathway on weight-for-age Z score (WAZ) over hospital length of stay (HLOS) for infants with congenital heart disease (CHD). STUDY DESIGN: A 10-year retrospective cohort study examined eligible infants who underwent neonatal cardiac surgery between July 2009 and December 2018 (n = 987). Eligibility criteria included infants born at least 37 weeks of gestation and a minimum birth weight of 2 kg who underwent cardiac surgery for CHD within the first 30 days of life. Using the best linear unbiased predictions from a linear mixed effects model, WAZ change over HLOS was estimated before and after January 2013, when the standardized feeding approach was initiated. The best linear unbiased predictions model included adjustment for patient characteristics including sex, race, HLOS, and class of cardiac defect. RESULTS: The change in WAZ over HLOS was significantly higher from 2013 to 2018 than from 2009 to 2012 (ß = 0.16; SE = 0.02; P < .001), after controlling for sex, race, HLOS, and CHD category, indicating that infants experienced a decreased WAZ loss over HLOS after the standardized feeding approach was initiated. Additionally, differences were found in WAZ loss over HLOS between infants with single ventricle CHD (ß = 0.26; SE = 0.04; P < .001) and 2 ventricle CHD (ß = 0.04; SE = 0.02; P = .04). CONCLUSIONS: These data suggest that an organized, focused approach for nutrition therapy using a standardized pathway improves weight change outcomes before hospital discharge for infants with single and 2 ventricle CHD who require neonatal cardiac surgery.

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OBJECTIVE: To detail common comorbidities and procedures performed to evaluate functional nausea in children. STUDY DESIGN: In total, 63 children age 7-18 years seen in a tertiary care pediatric clinic who met Rome IV criteria for functional nausea prospectively completed an Intake Questionnaire, the Pediatric and Parent-Proxy PROMIS-25 Profile v 2.0, the Pediatric and Parent-Proxy Pediatric Sleep Disturbance-Short Form 4a, and the COMPASS 31 orthostatic intolerance scale to assess comorbidities. Medical records were reviewed for diagnostic tests performed to evaluate nausea and for additional comorbidities. Summary statistics were used to determine the most common comorbidities and diagnostic yield of the procedures. Intraclass correlation coefficients assessed agreement between parent and child reports on the PROMIS scales. RESULTS: Patients with functional nausea experienced multisystem comorbidities. A majority reported abdominal pain, headache, orthostatic intolerance, fatigue, disturbed sleep, anxiety, constipation, allergies, and vomiting. Agreement between parent-proxy and child report of symptoms on PROMIS scales was good to excellent (intraclass correlation coefficients = .78-.83; all P < .001). Patients underwent extensive diagnostic testing: 96 endoscopic procedures, 199 radiologic tests, and 4 cholecystectomies. Most of the procedures were not diagnostically informative. CONCLUSIONS: Children with functional nausea have comorbidities outside the gastrointestinal tract that warrant evaluation. Gastrointestinal diagnostic tests were of low-yield in identifying a cause. Understanding the relationship with comorbidities may provide insight into etiologies for the nausea and define clinical phenotypes to better tailor care.

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