The Role of Science Advisory Boards in US Federal Health Policy

In the context of scarce financial resources for government programs in both the United States and internationally, efforts to develop health policies that are informed by evidence may increase in the coming years. In the United States, policymakers repeatedly attempt to integrate research and evidence into the policy process by establishing federal advisory committees (FACs) under the purview of the Federal Advisory Committee Act (FACA) of 1972. Although FACA committees have existed for 40 years, are used frequently by the executive branch, and have accounted for $3.4 billion in government spending between 2002 and 2011, they remain “little-known [and] little-studied” (McApline and LeDonne, 1993). Two case studies were conducted for this dissertation using a multiple-case study design and a grounded theory approach to data analysis. The overall aim was to describe how FACs play a role in the policy process. The two cases were the science advisory board to the President’s Emergency Plan for AIDS Relief and the National Climate Assessment and Development Advisory Committee, established by the US Department of State and the Department of Commerce, respectively. Semi-structured interviews were conducted with purposively-selected FAC members and staff from government agencies and non-governmental organizations (NGOs). Interview transcripts were coded using Atlas/ti following the grounded theory method outlined by Charmaz. Documents from FAC proceedings were also analyzed. Data collection was concluded when theoretical saturation was achieved. Findings suggest that FACA committees are heterogeneous in their primary objectives, operating structures, decision-making processes, and methods of engaging with NGOs. In addition, ambiguity in the FACA language and the politically sensitive nature of selecting members complicates efforts to establish a FAC. However, in spite of the differences across FACA committees and the difficulties encountered by government agencies when establishing them, findings indicate that FACs can be effective as mechanisms for agencies to obtain specific and broad guidance from independent experts on scientific matters of concern to the agency. The extent to which recommendations from FACs are adopted by the establishing agency is influenced by the perspectives of the executive and legislative branches on the value of evidence-based policy, as well as the perspective of the agency administrator

2013-2014 Chamber Music Palm Beach No. 3

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2015-2016 Mostly Music: Ravel and Friends

https://spiral.lynn.edu/conservatory_mostlymusic/1025/thumbnail.jp

Impact of Conditional Cash Transfers on Maternal and Newborn Health

Maternal and newborn health (MNH) is a high priority for global health and is included among the Millennium Development Goals (MDGs). However, the slow decline in maternal and newborn mortality jeopardizes achievements of the targets of MDGs. According to UNICEF, 60 million women give birth outside of health facilities, and family planning needs are satisfied for only 50%. Further, skilled birth attendance and the use of antenatal care are most inequitably distributed in maternal and newborn health interventions in low- and middle-income countries. Conditional cash transfer (CCT) programmes have been shown to increase health service utilization among the poorest but little is written on the effects of such programmes on maternal and newborn health. We carried out a systematic review of studies on CCT that report maternal and newborn health outcomes, including studies from 8 countries. The CCT programmes have increased antenatal visits, skilled attendance at birth, delivery at a health facility, and tetanus toxoid vaccination for mothers and reduced the incidence of low birthweight. The programmes have not had a significant impact on fertility while the impact on maternal and newborn mortality has not been welldocumented thus far. Given these positive effects, we make the case for further investment in CCT programmes for maternal and newborn health, noting gaps in knowledge and providing recommendations for better design and evaluation of such programmes. We recommend more rigorous impact evaluations that document impact pathways and take factors, such as cost-effectiveness, into account

Impact of Conditional Cash Transfers on Maternal and Newborn Health

Maternal and newborn health (MNH) is a high priority for global health and is included among the Millennium Development Goals (MDGs). However, the slow decline in maternal and newborn mortality jeopardizes achievements of the targets of MDGs. According to UNICEF, 60 million women give birth outside of health facilities, and family planning needs are satisfied for only 50%. Further, skilled birth attendance and the use of antenatal care are most inequitably distributed in maternal and newborn health interventions in low- and middle-income countries. Conditional cash transfer (CCT) programmes have been shown to increase health service utilization among the poorest but little is written on the effects of such programmes on maternal and newborn health. We carried out a systematic review of studies on CCT that report maternal and newborn health outcomes, including studies from 8 countries. The CCT programmes have increased antenatal visits, skilled attendance at birth, delivery at a health facility, and tetanus toxoid vaccination for mothers and reduced the incidence of low birthweight. The programmes have not had a significant impact on fertility while the impact on maternal and newborn mortality has not been well-documented thus far. Given these positive effects, we make the case for further investment in CCT programmes for maternal and newborn health, noting gaps in knowledge and providing recommendations for better design and evaluation of such programmes. We recommend more rigorous impact evaluations that document impact pathways and take factors, such as cost-effectiveness, into account

Achieving Health Equity Through Community Engagement in Translating Evidence to Policy: The San Francisco Health Improvement Partnership, 2010–2016

BACKGROUND: The San Francisco Health Improvement Partnership (SFHIP) promotes health equity by using a novel collective impact model that blends community engagement with evidence-to-policy translational science. The model involves diverse stakeholders, including ethnic-based community health equity coalitions, the local public health department, hospitals and health systems, a health sciences university, a school district, the faith community, and others sectors. COMMUNITY CONTEXT: We report on 3 SFHIP prevention initiatives: reducing consumption of sugar sweetened beverages (SSBs), regulating retail alcohol sales, and eliminating disparities in children’s oral health. METHODS: SFHIP is governed by a steering committee. Partnership working groups for each initiative collaborate to 1) develop and implement action plans emphasizing feasible, scalable, translational-science–informed interventions and 2) consider sustainability early in the planning process by including policy and structural interventions. OUTCOME: Through SFHIP’s efforts, San Francisco enacted ordinances regulating sale and advertising of SSBs and a ballot measure establishing a soda tax. Most San Francisco hospitals implemented or committed to implementing healthy-beverage policies that prohibited serving or selling SSBs. SFHIP helped prevent Starbucks and Taco Bell from receiving alcohol licenses in San Francisco and helped prevent state authorization of sale of powdered alcohol. SFHIP increased the number of primary care clinics providing fluoride varnish at routine well-child visits from 3 to 14 and acquired a state waiver to allow dental clinics to be paid for dental services delivered in schools. INTERPRETATION: The SFHIP model of collective impact emphasizing community engagement and policy change accomplished many of its intermediate goals to create an environment promoting health and health equity

2022-2023 New Beginnings

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Identification of germline monoallelic mutations in IKZF2 in patients with immune dysregulation

Helios, encoded by IKZF2, is a member of the Ikaros family of transcription factors with pivotal roles in T-follicular helper, NK- and T-regulatory cell physiology. Somatic IKZF2 mutations are frequently found in lymphoid malignancies. Although germline mutations in IKZF1 and IKZF3 encoding Ikaros and Aiolos have recently been identified in patients with phenotypically similar immunodeficiency syndromes, the effect of germline mutations in IKZF2 on human hematopoiesis and immunity remains enigmatic. We identified germline IKZF2 mutations (one nonsense (p.R291X)- and 4 distinct missense variants) in six patients with systemic lupus erythematosus, immune thrombocytopenia or EBV-associated hemophagocytic lymphohistiocytosis. Patients exhibited hypogammaglobulinemia, decreased number of T-follicular helper and NK cells. Single-cell RNA sequencing of PBMCs from the patient carrying the R291X variant revealed upregulation of proinflammatory genes associated with T-cell receptor activation and T-cell exhaustion. Functional assays revealed the inability of HeliosR291X to homodimerize and bind target DNA as dimers. Moreover, proteomic analysis by proximity-dependent Biotin Identification revealed aberrant interaction of 3/5 Helios mutants with core components of the NuRD complex conveying HELIOS-mediated epigenetic and transcriptional dysregulation.Peer reviewe

Cascaded Multi-View Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer\u27s Disease via Fusion of Clinical, Imaging and Omic Features

The introduction of mild cognitive impairment (MCI) as a diagnostic category adds to the challenges of diagnosing Alzheimer\u27s Disease (AD). No single marker has been proven to accurately categorize patients into their respective diagnostic groups. Thus, previous studies have attempted to develop fused predictors of AD and MCI. These studies have two main limitations. Most do not simultaneously consider all diagnostic categories and provide suboptimal fused representations using the same set of modalities for prediction of all classes. In this work, we present a combined framework, cascaded multiview canonical correlation (CaMCCo), for fusion and cascaded classification that incorporates all diagnostic categories and optimizes classification by selectively combining a subset of modalities at each level of the cascade. CaMCCo is evaluated on a data cohort comprising 149 patients for whom neurophysiological, neuroimaging, proteomic and genomic data were available. Results suggest that fusion of select modalities for each classification task outperforms (mean AUC = 0.92) fusion of all modalities (mean AUC = 0.54) and individual modalities (mean AUC = 0.90, 0.53, 0.71, 0.73, 0.62, 0.68). In addition, CaMCCo outperforms all other multi-class classification methods for MCI prediction (PPV: 0.80 vs. 0.67, 0.63)