Structured Application of Biological Ontologies to Annotate High-Throughput Screening Assays and their Targets of Activity

High-throughput screening (HTS) assays have changed the pace of chemical data collection, enabling assessments at various levels of biological relevance. EPA's ToxCast Program has 328 assays (experiments) generating 541 assay components (readouts), which produces 795 assay component endpoints (analyses), with intentions to increase the number of assays and the number of substances tested. As new assays are developed, it becomes a challenge to communicate what kind of data and features are associated with each assay. This report uses the BioAssay Ontology and other publicly available ontologies to produce the ToxCast Assay Annotation, a structured resource for descriptive information that uses controlled vocabulary to aid in the communication and use of ToxCast HTS assay data. Organized by 34 annotations including 'assay design type' and 'detection technology type', this structure allows for a concise reference to the pertinent attributes of an assay. Additionally, the perspective differences between the technological and intended target are separately captured. This structured annotation also allows for the identification of comparable ToxCast assay endpoints, and offers the potential to link with other HTS data repositories.Master of Science in Public Healt

Development of a social and environmental determinants of health informatics maturity model

INTRODUCTION: Integrating social and environmental determinants of health (SEDoH) into enterprise-wide clinical workflows and decision-making is one of the most important and challenging aspects of improving health equity. We engaged domain experts to develop a SEDoH informatics maturity model (SIMM) to help guide organizations to address technical, operational, and policy gaps. METHODS: We established a core expert group consisting of developers, informaticists, and subject matter experts to identify different SIMM domains and define maturity levels. The candidate model (v0.9) was evaluated by 15 informaticists at a Center for Data to Health community meeting. After incorporating feedback, a second evaluation round for v1.0 collected feedback and self-assessments from 35 respondents from the National COVID Cohort Collaborative, the Center for Leading Innovation and Collaboration\u27s Informatics Enterprise Committee, and a publicly available online self-assessment tool. RESULTS: We developed a SIMM comprising seven maturity levels across five domains: data collection policies, data collection methods and technologies, technology platforms for analysis and visualization, analytics capacity, and operational and strategic impact. The evaluation demonstrated relatively high maturity in analytics and technological capacity, but more moderate maturity in operational and strategic impact among academic medical centers. Changes made to the tool in between rounds improved its ability to discriminate between intermediate maturity levels. CONCLUSION: The SIMM can help organizations identify current gaps and next steps in improving SEDoH informatics. Improving the collection and use of SEDoH data is one important component of addressing health inequities

Toward informatics-enabled preparedness for natural hazards to minimize health impacts of climate change

Natural hazards (NHs) associated with climate change have been increasing in frequency and intensity. These acute events impact humans both directly and through their effects on social and environmental determinants of health. Rather than relying on a fully reactive incident response disposition, it is crucial to ramp up preparedness initiatives for worsening case scenarios. In this perspective, we review the landscape of NH effects for human health and explore the potential of health informatics to address associated challenges, specifically from a preparedness angle. We outline important components in a health informatics agenda for hazard preparedness involving hazard-disease associations, social determinants of health, and hazard forecasting models, and call for novel methods to integrate them toward projecting healthcare needs in the wake of a hazard. We describe potential gaps and barriers in implementing these components and propose some high-level ideas to address them

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

Enhancing Secondary-use of Electronic Health Records for Geospatial-temporal Population Health Research

Thesis (Ph.D.)--University of Washington, 2020For almost three decades, the United States Department of Human and Health Services, Center for Disease Control, and the World Health Organization have recognized the role of social and environmental determinants of health in understanding the health of populations. Community and population health is a function of each individual’s health and wellness, determined in large by their socioeconomic status, environmental factors, and access to healthcare services. In disastrous times, spatiotemporally-relevant information escalate in importance as health systems strive to address emergent concerns, pre-existing needs, population migration, while experiencing disruption in available resources and infrastructure. With their adoption by hospitals and health systems, Electronic Health Records (EHRs) contain a richness and diversity of information about patients. EHRs could inform where and how to prepare for population-scale patient needs in future disaster scenarios with a timely, equitable, and data-driven approach; however, the ability to apply spatiotemporal reasoning with EHRs have remained an underrepresented capacity. Informatics innovations would need to account for the operational, technical, and ethical constraints felt by those who study the health of populations. In this dissertation, I focus on three areas for building capacities to use of geospatial-temporal information to address population health needs. The aims are to: 1) assess information needs and priority use-cases for population health research in hydrologic disaster preparedness, 2) design spatiotemporal use-case workflows to survey trends and anomalies for regional areas using gridded hydrometeorological data products, a surrogate for structured multivariate datasets, and 3) develop an approach for spatiotemporal inferential statistics of EHR patient diagnosis information. This work incorporates flexible design and secondary-use of data for population health research and geographic inferences in preparation for future disasters

Severe Hyperphosphatemia in a Patient with Mild Acute Kidney Injury

Hyperphosphatemia may arise from various conditions including exogenous ingestion, extracellular shifts due to cell death or alterations in acid-base status, increased bone resorption, hormonal dysregulations leading to reduced renal excretion, reduced kidney function, or faulty measurement techniques. We herein present a case of a young pregnant woman who presented with mild acute kidney injury (AKI), invasive mucormycosis receiving liposomal amphotericin, and hyperphosphatemia out of proportion to the degree of kidney injury. While the patient was given routine phosphate-binding agent by her primary care team for presumed AKI-associated hyperphosphatemia, a full investigation by the renal consulting team for contributing factors other than kidney injury revealed that she actually had pseudohyperphosphatemia associated with the use of liposomal amphotericin. Erroneous treatment of pseudohyperphosphatemia may have been detrimental to this pregnant patient. A literature review for conditions associated with pseudohyperphosphatemia other than the use of liposomal amphotericin will be discussed

ToxCast Assay Network (TCAN) Viewer: A Visualization Tool for High-throughput Assay Chemical Data

<table><tbody><tr> <td>Presented at the Annual Society of Toxicology meeting</td></tr></tbody></table

ToxCast Assay Network (TCAN) Viewer: A Big-Picture Visualization Tool for High-throughput Assays and Environmental Chemicals

ToxCast Assay Network (TCAN) Viewer: A Big-Picture Visualization Tool for High-throughput Assays and Environmental Chemical