Pediatric Epilepsy Learning Healthcare System Quality of Life (PELHS-QOL-2): A novel health-related quality of life prompt for children with epilepsy.

OBJECTIVE: Pediatric epilepsy is often associated with diminished health-related quality of life (HRQOL). Our aim was to establish the validity of the Pediatric Epilepsy Learning Healthcare System Quality of Life (PELHS-QOL-2) questions, a novel two-item HRQOL prompt for children with epilepsy, primarily for use in clinical care. METHODS: We performed a multicenter cross-sectional study to validate the PELHS-QOL-2. Construct validity was established through bivariate comparisons with four comparator measures and known drivers of quality of life in children with epilepsy, as well as by creating an a priori multivariable model to predict the Quality of Life in Childhood Epilepsy Questionnaire (QOLCE-55). Validity generalization was established through bivariate comparisons with demographic and clinical information. Content validity and clinical utility were established by assessing how well the PELHS-QOL-2 met eight design criteria for an HRQOL prompt established by a multistakeholder group of experts. RESULTS: The final participant sample included 154 English-speaking caregivers of children with epilepsy (mean age = 9.7 years, range = .5-18, 49% female, 70% White). The PELHS-QOL-2 correlated with the four comparator instruments (ρ = .44-.56), was significantly associated with several known drivers of quality of life in children with epilepsy (p < .05), and predicted QOLCE-55 scores in the multivariate model (adjusted R2 = .54). The PELHS-QOL-2 item was not associated with the age, sex, and ethnicity of the children nor with the setting and location of data collection, although PELHS-QOL-Medications was significantly associated with race (worse for White race). Following both quantitative and qualitative analysis, the PELHS-QOL-2 met seven of eight design criteria. SIGNIFICANCE: The PELHS-QOL-2 is a valid HRQOL prompt and is well suited for use in clinical care as a mechanism to routinely initiate conversations with caregivers about quality of life in children with epilepsy. The association of PELHS-QOL-Medications with race merits further study.

Why secret detection tools are not enough: It's not just about false positives - An industrial case study.

Checked-in secrets in version-controlled software projects pose security risks to software and services. Secret detection tools can identify the presence of secrets in the code, commit changesets, and project version control history. As these tools can generate false positives, developers are provided with mechanisms to bypass the warnings generated from these tools. Providing this override mechanism can result in developers sometimes exposing secrets in software repositories. The goal of this article is to aid software security practitioners in understanding why' secrets are checked into repositories, despite being warned by tools, through an industrial case study of analysis of usage data of a secret detection tool and a survey of developers who bypassed the tool alert. In this case study, we analyzed the usage data of a checked-in secret detection tool used widely by a software company and we surveyed developers who bypassed the warnings generated by the tool. From the case study, we found that, despite developers classified 50% of the warning as false positive, developers also bypassed the warning due to time constraints, working with non-shipping projects, technical challenges of eliminating secrets completely from the version control history, technical debts, and perceptions that check-ins are low risk. We advocate practitioners and researchers to investigate the findings of our study further to improve secret detection tools and related development practices. We also advocate that organizations should insert secondary checks, as is done by the company we studied, to capture occasions where developers incorrectly bypass secret detection tools.

Design and implementation of electronic health record common data elements for pediatric epilepsy: Foundations for a learning health care system.

OBJECTIVE: Common data elements (CDEs) are standardized questions and answer choices that allow aggregation, analysis, and comparison of observations from multiple sources. Clinical CDEs are foundational for learning health care systems, a data-driven approach to health care focused on continuous improvement of outcomes. We aimed to create clinical CDEs for pediatric epilepsy. METHODS: A multiple stakeholder group (clinicians, researchers, parents, caregivers, advocates, and electronic health record [EHR] vendors) developed clinical CDEs for routine care of children with epilepsy. Initial drafts drew from clinical epilepsy note templates, CDEs created for clinical research, items in existing registries, consensus documents and guidelines, quality metrics, and outcomes needed for demonstration projects. The CDEs were refined through discussion and field testing. We describe the development process, rationale for CDE selection, findings from piloting, and the CDEs themselves. We also describe early implementation, including experience with EHR systems and compatibility with the International League Against Epilepsy classification of seizure types. RESULTS: Common data elements were drafted in August 2017 and finalized in January 2020. Prioritized outcomes included seizure control, seizure freedom, American Academy of Neurology quality measures, presence of common comorbidities, and quality of life. The CDEs were piloted at 224 visits at 10 centers. The final CDEs included 36 questions in nine sections (number of questions): diagnosis (1), seizure frequency (9), quality of life (2), epilepsy history (6), etiology (8), comorbidities (2), treatment (2), process measures (5), and longitudinal history notes (1). Seizures are categorized as generalized tonic-clonic (regardless of onset), motor, nonmotor, and epileptic spasms. Focality is collected as epilepsy type rather than seizure type. Seizure frequency is measured in nine levels (all used during piloting). The CDEs were implemented in three vendor systems. Early clinical adoption included 1294 encounters at one center. SIGNIFICANCE: We created, piloted, refined, finalized, and implemented a novel set of clinical CDEs for pediatric epilepsy.

Access to Home- and Community-Based Services for Children with Disability: Academic Institutions' Role and Areas for Improvement.

OBJECTIVE: This project sought to describe provider- and parent-identified needs and barriers to obtaining home- and community-based services (HCBS) for children with disability (CWD) and to determine ways pediatric health care institutions can improve access to HCBS services. METHODS: In this exploratory sequential mixed methods evaluation, semi-structured interviews and focus groups were conducted with multidisciplinary providers and staff from an independent children's hospital, followed by a survey of English and Spanish-speaking parents of CWD. Data from interviews and surveys were then triangulated for overarching common themes regarding how pediatric health care institutions can better support access to HCBS. RESULTS: Among 382 parent respondents, 74.1% reported that their child needed a HCBS, most commonly physical/occupational/speech therapies, school-based support, and case management services. Two-thirds of parents reported at least one barrier to accessing HCBS and one-third experience >3 barriers. While multiple current institutional strengths were noted, internal weaknesses included lack of provider knowledge, staffing difficulties, and lack of protocols for identifying and tracking patients needing or receiving HCBS. External threats included requirements to entry for HCBS and transfer of care, with opportunities for improvement involving dissemination of information, funding support, and connection between providers/support staff and services. CONCLUSIONS: Parents of CWD identified HCBS as necessary for the health of this population, but multiple barriers to HCBS were identified by both parents and providers. Multiple internal and external opportunities for improvement relative to pediatric health care institutions were identified, suggesting a need for a comprehensive approach to ensure that CWD receive necessary HCBS.

PediHome: Development of a Family-Reported Measure of Pediatric Home Healthcare Quality.

OBJECTIVE: No validated tools exist to measure pediatric home healthcare quality. The objective of this work was to develop a family-reported survey (PediHome) to measure the quality of home healthcare for children with medical complexity (CMC). METHODS: A national multidisciplinary expert panel (N = 19) was convened to develop survey content domains. Panelist were joined by 3 additional experts to rank candidate survey items for importance and evaluate relevance and structure. Cognitive interviews were conducted with English-speaking (n = 12) and Spanish-speaking (n = 4) family caregivers of CMC to revise problematic items and clarify response options. A cross-sectional survey was then fielded (6/1/20-10/31/20) to parents whose children receive healthcare at 2 regional academic medical centers. RESULTS: The final measure included N = 28 total items with 4 items quantifying access, 1 evaluating overall quality rating, and 21 items assessing provider tasks (11 home nursing only, 2 certified nursing assistant/home health aide only, and 1 dual). Out of 312 caregivers of CMC, 142 (46%) responded and one-half (n = 68, 48%) reported a child receiving home nursing. They received a weekly median of 58.4% (IQR ±31.2%) of approved nursing hours with 55% reporting a missed nursing shift within the last month. Median overall quality was 75-9 (0-10 scale) and median scores on specific quality items ranged from 31-4 to 43-4 (0-4 scale). CONCLUSIONS: PediHome is a new content-valid family-reported measure of home healthcare quality for CMC that is useful for evaluating healthcare quality across several domains. Future work will involve assessing PediHome's construct and predictive validity.

BioPortal: ontologies and integrated data resources at the click of a mouse.

Biomedical ontologies provide essential domain knowledge to drive data integration, information retrieval, data annotation, natural-language processing and decision support. BioPortal (http://bioportal.bioontology.org) is an open repository of biomedical ontologies that provides access via Web services and Web browsers to ontologies developed in OWL, RDF, OBO format and Protégé frames. BioPortal functionality includes the ability to browse, search and visualize ontologies. The Web interface also facilitates community-based participation in the evaluation and evolution of ontology content by providing features to add notes to ontology terms, mappings between terms and ontology reviews based on criteria such as usability, domain coverage, quality of content, and documentation and support. BioPortal also enables integrated search of biomedical data resources such as the Gene Expression Omnibus (GEO), ClinicalTrials.gov, and ArrayExpress, through the annotation and indexing of these resources with ontologies in BioPortal. Thus, BioPortal not only provides investigators, clinicians, and developers 'one-stop shopping' to programmatically access biomedical ontologies, but also provides support to integrate data from a variety of biomedical resources.

Implementing an integrated multi-technology platform for drug checking: Social, scientific, and technological considerations.

The illicit drug overdose crisis in North America continues to devastate communities with fentanyl detected in the majority of illicit drug overdose deaths. The COVID-19 pandemic has heightened concerns of even greater unpredictability in the drug supplies and unprecedented rates of overdoses. Portable drug-checking technologies are increasingly being integrated within overdose prevention strategies. These emerging responses are raising new questions about which technologies to pursue and what service models can respond to the current risks and contexts. In what has been referred to as the epicenter of the overdose crisis in Canada, a multi-technology platform for drug checking is being piloted in community settings using a suite of chemical analytical methods to provide real-time harm reduction. These include infrared absorption, Raman scattering, gas chromatography with mass spectrometry, and antibody-based test strips. In this Perspective, we illustrate some advantages and challenges of using multiple techniques for the analysis of the same sample, and provide an example of a data analysis and visualization platform that can unify the presentation of the results and enable deeper analysis of the results. We also highlight the implementation of a various service models that co-exist in a research setting, with particular emphasis on the way that drug checking technicians and harm reduction workers interact with service users. Finally, we provide a description of the challenges associated with data interpretation and the communication of results to a diverse audience.

How information visualization novices construct visualizations.

It remains challenging for information visualization novices to rapidly construct visualizations during exploratory data analysis. We conducted an exploratory laboratory study in which information visualization novices explored fictitious sales data by communicating visualization specifications to a human mediator, who rapidly constructed the visualizations using commercial visualization software. We found that three activities were central to the iterative visualization construction process: data attribute selection, visual template selection, and visual mapping specification. The major barriers faced by the participants were translating questions into data attributes, designing visual mappings, and interpreting the visualizations. Partial specification was common, and the participants used simple heuristics and preferred visualizations they were already familiar with, such as bar, line and pie charts. We derived abstract models from our observations that describe barriers in the data exploration process and uncovered how information visualization novices think about visualization specifications. Our findings support the need for tools that suggest potential visualizations and support iterative refinement, that provide explanations and help with learning, and that are tightly integrated into tool support for the overall visual analytics process.

National Center for Biomedical Ontology: advancing biomedicine through structured organization of scientific knowledge.

The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease.

Activity intolerance and impaired physical mobility in elders.

PURPOSE: To clarify the use of two nursing diagnoses, activity intolerance and impaired physical mobility, with elderly patients. METHOD: Ninety-two elders from a long-term care facility in Wonju, Korea. A checklist developed by the researchers was used for data collection. FINDINGS: Defining characteristics from this study related to psychological components of activity intolerance are significant in differentiating between the two diagnoses. Using a decision-making tree based on data from this study, each nursing diagnosis can be correctly identified. CONCLUSIONS: The results of this study are significant in broadening the defining characteristics to be used in differentiating between two nursing diagnoses. PRACTICE IMPLICATIONS: Clarification of nursing diagnoses serves to direct students and nurses to choosing appropriate interventions.

Ontologies in biological data visualization.

In computer science, an ontology is essentially a graph-based knowledge representation in which each node corresponds to a concept and each edge specifies a relation between two concepts. Ontological development in biology can serve as a focus to discuss the challenges and possible research directions for ontologies in visualization. The principle challenges are the dynamic and evolving nature of ontologies, the ever-present issue of scale, the diversity and richness of the relationships in ontologies, and the need to better understand the relationship between ontologies and the data analysis tasks scientists wish to support. Research directions include visualizing ontologies; visualizing semantically or ontologically annotated texts, documents, and corpora; automated generation of visualizations using ontologies; and visualizing ontological context to support search. Although this discussion uses issues of ontologies in biological data visualization as a springboard, these topics are of general relevance to visualization.

Supporting the Collaborative Authoring of ICD-11 with WebProtégé.

The World Health Organization (WHO) is well under way with the new revision of the International Classification of Diseases (ICD-11). The current revision process is significantly different from past ones: the ICD-11 authoring is now open to a large international community of medical experts, who perform the authoring in a web-based collaborative platform. The classification is also embracing a more formal representation that is suitable for electronic health records. We present the ICD Collaborative Authoring Tool (iCAT), a customization of the WebProtégé editor that supports the community based authoring of ICD-11 on the Web and provides features such as discussion threads integrated in the authoring process, change tracking, content reviewing, and so on. The WHO editors evaluated the initial version of iCAT and found the tool intuitive and easy to learn. They also identified improvement potentials and new requirements for large-scale collaboration support. A demo version of the tool is available at: http://icatdemo.stanford.edu.

An interactive tool for visualizing design heterogeneity in clinical trials.

Clinical questions are often studied by randomized clinical trials (RCTs) of heterogeneous design. Systematic reviewers and trial designers need to compare the design and results across these trials. If trial information is available in computer processable form, computer-based visualization techniques can provide cognitive support for such comparisons. CTeXplorer offers systematic reviewers and trial designers a tool to better and more quickly understand design heterogeneity in RCTs. CTeXplorer supports dynamic queries on eligibility criteria, interventions, and outcomes in three linked views. We tested CTeXplorer for displaying 12 RCTs on prevention of mother-to-child transmission of HIV. Three target users found the representation and organization of information intuitive and easy to learn. They were able to use CTeXplorer to achieve a quick cognitive overview of a heterogeneous group of RCTs. This work shows the benefit of capturing trial information in computable form. Future work includes leveraging ontologies to enhance CTeXplorer visualizations.