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Metabolic dysfunction-associated steatohepatitis (MASH) is a major cause of liver-related morbidity and mortality, yet treatment options are limited. Manual scoring of liver biopsies, currently the gold standard for clinical trial enrollment and endpoint assessment, suffers from high reader variability. This study represents the most comprehensive multisite analytical and clinical validation of an artificial intelligence (AI)-based pathology system, AI-based measurement of metabolic dysfunction-associated steatohepatitis (AIM-MASH), to assist pathologists in MASH trial histology scoring. AIM-MASH demonstrated high repeatability and reproducibility compared to manual scoring. AIM-MASH-assisted reads by expert MASH pathologists were superior to unassisted reads in accurately assessing inflammation, ballooning, MAS ≥ 4 with ≥1 in each score category and MASH resolution, while maintaining non-inferiority in steatosis and fibrosis assessment. These findings suggest that AIM-MASH could mitigate reader variability, providing a more reliable assessment of therapeutics in MASH clinical trials.

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.

BackgroundSynergies between technology and health care in the United States are accelerating, increasing opportunities to leverage these technologies to improve patient care.MethodsThis 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.ResultsOf 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.ConclusionsBidirectional 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.

BackgroundTelemedicine 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.ObjectiveThe 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 methodsCase 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.FindingsData 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.ConclusionGreenlandic 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.

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.

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.

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.

To identify differential trajectories of neurocognitive outcomes following pediatric concussion and investigate predictors associated with patterns of recovery up to 3 months. 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. 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). 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. [ABSTRACT FROM AUTHOR]

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.