Longitudinal neurocognitive trajectories and risk factors in the first three months following pediatric concussion.

OBJECTIVE: To identify differential trajectories of neurocognitive outcomes following pediatric concussion and investigate predictors associated with patterns of recovery up to 3 months. METHODS: 74 participants aged 8-17 years completed attention/working memory, processing speed, and executive function measures at 2 weeks, 1 month, and 3 months post-injury. We used principal component analysis to generate a composite of information processing. Group-based trajectory modeling identified latent trajectories. Multinominal logistic regression was used to examine associations between risk factors and trajectory groups. RESULTS: We identified three trajectories of neurocognitive outcomes. The medium (54.6%) and high improving groups (35.8%) showed ongoing increase in information processing, while the low persistent group showed limited change 3 months post-injury. This group recorded below average scores on Digit Span Forward and Backward at 3 months. History of pre-injury headache was significantly associated with the persistent low scoring group, relative to the medium improving (p = 0.03) but not the high improving group (p = 0.09). CONCLUSIONS: This study indicates variability in neurocognitive outcomes according to three differential trajectories, with groups partially distinguished by preexisting child factors (history of frequent headaches). Modelling that accounts for heterogeneity in individual outcomes is essential to identify clinically meaningful indices that are indicative of children requiring intervention.

Exploring the deep learning of artificial intelligence in nursing: a concept analysis with Walker and Avant's approach.

BACKGROUND: In recent years, increased attention has been given to using deep learning (DL) of artificial intelligence (AI) in healthcare to address nursing challenges. The adoption of new technologies in nursing needs to be improved, and AI in nursing is still in its early stages. However, the current literature needs more clarity, which affects clinical practice, research, and theory development. This study aimed to clarify the meaning of deep learning and identify the defining attributes of artificial intelligence within nursing. METHODS: We conducted a concept analysis of the deep learning of AI in nursing care using Walker and Avant's 8-step approach. Our search strategy employed Boolean techniques and MeSH terms across databases, including BMC, CINAHL, ClinicalKey for Nursing, Embase, Ovid, Scopus, SpringerLink and Spinger Nature, ProQuest, PubMed, and Web of Science. By focusing on relevant keywords in titles and abstracts from articles published between 2018 and 2024, we initially found 571 sources. RESULTS: Thirty-seven articles that met the inclusion criteria were analyzed in this study. The attributes of evidence included four themes: focus and immersion, coding and understanding, arranging layers and algorithms, and implementing within the process of use cases to modify recommendations. Antecedents, unclear systems and communication, insufficient data management knowledge and support, and compound challenges can lead to suffering and risky caregiving tasks. Applying deep learning techniques enables nurses to simulate scenarios, predict outcomes, and plan care more precisely. Embracing deep learning equipment allows nurses to make better decisions. It empowers them with enhanced knowledge while ensuring adequate support and resources essential for caregiver and patient well-being. Access to necessary equipment is vital for high-quality home healthcare. CONCLUSION: This study provides a clearer understanding of the use of deep learning in nursing and its implications for nursing practice. Future research should focus on exploring the impact of deep learning on healthcare operations management through quantitative and qualitative studies. Additionally, developing a framework to guide the integration of deep learning into nursing practice is recommended to facilitate its adoption and implementation.

From patients to partners: participant-centric initiatives in biomedical research.

Advances in computing technology and bioinformatics mean that medical research is increasingly characterized by large international consortia of researchers that are reliant on large data sets and biobanks. These trends raise a number of challenges for obtaining consent, protecting participant privacy concerns and maintaining public trust. Participant-centred initiatives (PCIs) use social media technologies to address these immediate concerns, but they also provide the basis for long-term interactive partnerships. Here, we give an overview of this rapidly moving field by providing an analysis of the different PCI approaches, as well as the benefits and challenges of implementing PCIs.

My46: a Web-based tool for self-guided management of genomic test results in research and clinical settings.

A major challenge to implementing precision medicine is the need for an efficient and cost-effective strategy for returning individual genomic test results that is easily scalable and can be incorporated into multiple models of clinical practice. My46 is a Web-based tool for managing the return of genetic results that was designed and developed to support a wide range of approaches to disclosing results, ranging from traditional face-to-face disclosure to self-guided models. My46 has five key functions: set and modify results-return preferences, return results, educate, manage the return of results, and assess the return of results. These key functions are supported by six distinct modules and a suite of features that enhance the user experience, ease site navigation, facilitate knowledge sharing, and enable results-return tracking. My46 is a potentially effective solution for returning results and supports current trends toward shared decision making between patients and providers and patient-driven health management.Genet Med 19 4, 467-475.

Telemedicine in Greenland: Citizens' Perspectives.

BACKGROUND: Telemedicine may have the possibility to provide better access to healthcare delivery for the citizens. Telemedicine in arctic remote areas must be tailored according to the needs of the local population. Therefore, we need more knowledge about their needs and their view of telemedicine. OBJECTIVE: The aim of this study has been to explore how citizens living in the Greenlandic settlements experience the possibilities and challenges of telemedicine when receiving healthcare delivery in everyday life. MATERIALS AND METHODS: Case study design was chosen as the overall research design. Qualitative interviews (n = 14) were performed and participant observations (n = 80 h) carried out in the local healthcare center in the settlements and towns. A logbook was kept and updated each day during the field research in Greenland. Observations were made of activities in the settlements. FINDINGS: Data collected on citizens' views about the possibilities of using telemedicine in Greenland revealed the following findings: Greenlandic citizens are positive toward telemedicine, and telemedicine can help facilitate improved access to healthcare for residents in these Greenlandic settlements. Regarding challenges in using telemedicine in Greenland, the geographical and cultural context hinders accessibility to the Greenlandic healthcare system, and telemedicine equipment is not sufficiently mobile. CONCLUSION: Greenlandic citizens are positive toward telemedicine and regard telemedicine as a facilitator for improved access for healthcare in the Greenlandic settlements. We have identified challenges, such as geographical and cultural context, that hinder accessibility to the Greenlandic healthcare system.

Personalized Telehealth in the Future: A Global Research Agenda.

As telehealth plays an even greater role in global health care delivery, it will be increasingly important to develop a strong evidence base of successful, innovative telehealth solutions that can lead to scalable and sustainable telehealth programs. This paper has two aims: (1) to describe the challenges of promoting telehealth implementation to advance adoption and (2) to present a global research agenda for personalized telehealth within chronic disease management. Using evidence from the United States and the European Union, this paper provides a global overview of the current state of telehealth services and benefits, presents fundamental principles that must be addressed to advance the status quo, and provides a framework for current and future research initiatives within telehealth for personalized care, treatment, and prevention. A broad, multinational research agenda can provide a uniform framework for identifying and rapidly replicating best practices, while concurrently fostering global collaboration in the development and rigorous testing of new and emerging telehealth technologies. In this paper, the members of the Transatlantic Telehealth Research Network offer a 12-point research agenda for future telehealth applications within chronic disease management.

Characterizing Data Discovery and End-User Computing Needs in Clinical Translational Science.

In this paper, the authors present the results of a qualitative case-study seeking to characterize data discovery needs and barriers of principal investigators and research support staff in clinical translational science. Several implications for designing and implementing translational research systems have emerged through the authors' analysis. The results also illustrate the benefits of forming early partnerships with scientists to better understand their workflow processes and end-user computing practices in accessing data for research. The authors use this user-centered, iterative development approach to guide the implementation and extension of i2b2, a system they have adapted to support cross-institutional aggregate anonymized clinical data querying. With ongoing evaluation, the goal is to maximize the utility and extension of this system and develop an interface that appropriately fits the swiftly evolving needs of clinical translational scientists.

Check the Blood Pressure!: An Educational Tool for Anesthesiology Trainees Converting Epidural Labor Analgesia to Cesarean Delivery Anesthesia.

Recognition and treatment of maternal hypotension during epidural anesthesia administration for intrapartum cesarean delivery preserves maternal-fetal perfusion. A case that required quality assurance review uncovered lapses in maternal hemodynamic monitoring during the transition to intrapartum cesarean delivery anesthesia. To address this, a practice outline was designed for trainee's education describing intrapartum epidural dosing for cesarean delivery and adequate blood pressure monitoring. The time-lapse between epidural dosing and subsequent blood pressure was evaluated before and after the introduction of our educational tool. The time-lapse between blood pressure measures decreased to <10 minutes (10.78-13.92 vs 8.8-9.76 minutes).

Short-term effectiveness of intravitreal bevacizumab versus ranibizumab injections for patients with neovascular age-related macular degeneration.

PURPOSE: To compare the effectiveness of three consecutive intravitreal injections of bevacizumab (Avastin) and ranibizumab (Lucentis) in patients with treatment-naïve neovascular age-related macular degeneration. METHODS: This is a retrospective comparative study of qualifying consecutively treated patients (n = 176) with new-onset subfoveal choroidal neovascularization presenting at 6 retina referral centers. Patients were treated with 3 consecutive monthly injections of ranibizumab (0.5 mg) or 3 injections of bevacizumab every 6 weeks (1.25 mg) as determined by physician and patient preference. Ophthalmologic evaluations included monthly visual acuity measurements, ocular examinations, and optical coherence tomography imaging at each visit. RESULTS: A 29.2% reduction in the mean central foveal thickness measurement through optical coherence tomography was found in the ranibizumab-treated patients versus a 20.9% reduction in the bevacizumab-treated patients (P

Advances in Sharing Multi-sourced Health Data on Decision Support Science 2016-2017.

INTRODUCTION: Clinical decision support science is expanding to include integration from broader and more varied data sources, diverse platforms and delivery modalities, and is responding to emerging regulatory guidelines and increased interest from industry. OBJECTIVE: Evaluate key advances and challenges of accessing, sharing, and managing data from multiple sources for development and implementation of Clinical Decision Support (CDS) systems in 2016-2017. METHODS: Assessment of literature and scientific conference proceedings, current and pending policy development, and review of commercial applications nationally and internationally. RESULTS: CDS research is approaching multiple landmark points driven by commercialization interests, emerging regulatory policy, and increased public awareness. However, the availability of patient-related "Big Data" sources from genomics and mobile health, expanded privacy considerations, applications of service-based computational techniques and tools, the emergence of "app" ecosystems, and evolving patient-centric approaches reflect the distributed, complex, and uneven maturity of the CDS landscape. Nonetheless, the field of CDS is yet to mature. The lack of standards and CDS-specific policies from regulatory bodies that address the privacy and safety concerns of data and knowledge sharing to support CDS development may continue to slow down the broad CDS adoption within and across institutions. CONCLUSION: Partnerships with Electronic Health Record and commercial CDS vendors, policy makers, standards development agencies, clinicians, and patients are needed to see CDS deployed in the evolving learning health system.

Bidirectional Text Messaging to Improve Adherence to Recommended Lipid Testing.

BACKGROUND: Synergies between technology and health care in the United States are accelerating, increasing opportunities to leverage these technologies to improve patient care. METHODS: This study was a collaboration between an academic study team, a rural primary care clinic, and a local nonprofit informatics company developing tools to improve patient care through population management. Our team created a text messaging management tool, then developed methods for and tested the feasibility of bidirectional text messaging to remind eligible patients about the need for lipid testing. We measured patient response to the text messages, then interviewed 8 patients to explore their text messaging experience. RESULTS: Of the 129 patients the clinic was able to contact by phone, 29.4% had no cell phone or text-messaging capabilities. An additional 20% refused to participate. Two thirds of the 28 patients who participated in the text messaging intervention (67.9%) responded to at least 1 of the up to 3 messages. Seven of 8 interviewed patients had a positive text-messaging experience. CONCLUSIONS: Bidirectional text messaging is a feasible and largely acceptable form of communication for test reminders that has the potential to reach large numbers of patients in clinical care.

Building a Central Repository for Research Ethics Consultation Data: A Proposal for a Standard Data Collection Tool.

Clinical research ethics consultation services have been established across academic health centers over the past decade. This paper presents the results of collaboration within the CTSA consortium to develop a standard approach to the collection of research ethics consultation information to serve as a foundation for quality improvement, education, and research efforts. This approach includes categorizing and documenting descriptive information about the requestor, research project, the ethical question, the consult process, and describing the basic structure for a consult note. This paper also explores challenges in determining how to share some of this information between collaborating institutions related to concerns about confidentially, data quality, and informatics. While there is much still to be learned to improve the process of clinical research ethics consultation, these tools can advance these efforts, which, in turn, can facilitate the ethical conduct of research.

Dr. Jekyll's waiver of Mr. Hyde's right to refuse medical treatment: Washington's new law authorizing mental health care advance directives needs additional protection.

Mental health care advance directives are gaining popularity nationwide. Following a growing trend, the Washington State Legislature has recently passed a law allowing patients to draft mental health care advance directives that could be irrevocable. Patients who sign an irrevocable directive essentially waive their fundamental right to refuse treatment in the future. The United States Supreme Court has held that waivers of fundamental rights must be made knowingly, voluntarily, and intelligently. However, as passed, Washington's new law contains insufficient safeguards to guarantee such a waiver. This Comment proposes that the Washington State Legislature amend this law the require two additional protections: a "rights advocate" to explain the potential waiver of rights, and a written warning in the advance directive form. These safeguards will help ensure that patients make knowing and intelligent waivers of their fundamental right to refuse treatment.

Developing on-demand secure high-performance computing services for biomedical data analytics.

We propose a technical and process model to support biomedical researchers requiring on-demand high performance computing on potentially sensitive medical datasets. Our approach describes the use of cost-effective, secure and scalable techniques for processing medical information via protected and encrypted computing clusters within a model High Performance Computing (HPC) environment. The process model supports an investigator defined data analytics platform capable of accepting secure data migration from local clinical research data silos into a dedicated analytic environment, and secure environment cleanup upon completion. We define metrics to support the evaluation of this pilot model through performance and stability tests, and describe evaluation of its suitability towards enabling rapid deployment by individual investigators.

Practices and perspectives on building integrated data repositories: results from a 2010 CTSA survey.

Clinical integrated data repositories (IDRs) are poised to become a foundational element of biomedical and translational research by providing the coordinated data sources necessary to conduct retrospective analytic research and to identify and recruit prospective research subjects. The Clinical and Translational Science Award (CTSA) consortium's Informatics IDR Group conducted a survey of 2010 consortium members to evaluate recent trends in IDR implementation and use to support research between 2008 and 2010. A web-based survey based in part on a prior 2008 survey was developed and deployed to 46 national CTSA centers. A total of 35 separate organizations completed the survey (74%), representing 28 CTSAs and the National Institutes of Health Clinical Center. Survey results suggest that individual organizations are progressing in their approaches to the development, management, and use of IDRs as a means to support a broad array of research. We describe the major trends and emerging practices below.

Brainstorming Design for Health: Helping Patients Utilize Patient-Generated Information on the Web.

Researchers and practitioners show increasing sinterest in utilizing patient-generated information on the Web. Although the HCI and CSCW communities have provided many exciting opportunities for exploring new ideas and building broad agenda in health, few venues offer a platform for interdisciplinary and collaborative brainstorming about design challenges and opportunities in this space. The goal of this workshop is to provide participants with opportunities to interact with stakeholders from diverse backgrounds and practices-researchers, practitioners, designers, programmers, and ethnographers-and together generate tangible design outcomes that utilize patient-generated information on the Web. Through small multidisciplinary group work, we will provide participants with new collaboration opportunities, understanding of the state of the art, inspiration for future work, and ideally avenues for continuing to develop research and design ideas generated at the workshop.

Using RxNorm for cross-institutional formulary data normalization within a distributed grid-computing environment.

Within the CTSA (Clinical Translational Sciences Awards) program, academic medical centers are tasked with the storage of clinical formulary data within an Integrated Data Repository (IDR) and the subsequent exposure of that data over grid computing environments for hypothesis generation and cohort selection. Formulary data collected over long periods of time across multiple institutions requires normalization of terms before those data sets can be aggregated and compared. This paper sets forth a solution to the challenge of generating derived aggregated normalized views from large, distributed data sets of clinical formulary data intended for re-use within clinical translational research.

Ontology mapping and data discovery for the translational investigator.

An integrated data repository (IDR) containing aggregations of clinical, biomedical, economic, administrative, and public health data is a key component of an overall translational research infrastructure. But most available data repositories are designed using standard data warehouse architecture that employs arbitrary data encoding standards, making queries across disparate repositories difficult. In response to these shortcomings we have designed a Health Ontology Mapper (HOM) that translates terminologies into formal data encoding standards without altering the underlying source data. We believe the HOM system promotes inter-institutional data sharing and research collaboration, and will ultimately lower the barrier to developing and using an IDR.

Ipsilateral directional encoding of joystick movements in human cortex.

The majority of Brain Computer Interfaces have relied on signals related to primary motor cortex and the operation of the contralateral limb. Recently, the physiology associated with same-sided (ipsilateral) motor movements has been found to have a unique cortical physiology. This study sets out to assess whether more complex motor movements can be discerned utilizing ipsilateral cortical signals. In this study, three invasively monitored human subjects were recorded while performing a center out joystick task with the hand ipsilateral to the hemispheric subdural grid array. It was found that directional tuning was present in ipsilateral cortex. This information was encoded in both distinct anatomic populations and spectral distributions. These findings support the notion that ipsilateral signals may provide added information for BCI operation in the future.

Synergies and distinctions between computational disciplines in biomedical research: perspective from the Clinical andTranslational Science Award programs.

Clinical and translational research increasingly requires computation. Projects may involve multiple computationally oriented groups including information technology (IT) professionals, computer scientists, and biomedical informaticians. However, many biomedical researchers are not aware of the distinctions among these complementary groups, leading to confusion, delays, and suboptimal results. Although written from the perspective of Clinical and Translational Science Award (CTSA) programs within academic medical centers, this article addresses issues that extend beyond clinical and translational research. The authors describe the complementary but distinct roles of operational IT, research IT, computer science, and biomedical informatics using a clinical data warehouse as a running example. In general, IT professionals focus on technology. The authors distinguish between two types of IT groups within academic medical centers: central or administrative IT (supporting the administrative computing needs of large organizations) and research IT (supporting the computing needs of researchers). Computer scientists focus on general issues of computation such as designing faster computers or more efficient algorithms, rather than specific applications. In contrast, informaticians are concerned with data, information, and knowledge. Biomedical informaticians draw on a variety of tools, including but not limited to computers, to solve information problems in health care and biomedicine. The paper concludes with recommendations regarding administrative structures that can help to maximize the benefit of computation to biomedical research within academic health centers.