Developing the Standardized Workload Assessment Metric for Pediatric Emergency Departments: Initial Steps Using a Modified Delphi Method.

Objectives: We aimed to develop a comprehensive list of patient care components performed by pediatric emergency department (PED) physicians that could be individually scored on their subjective workload using the National Aeronautics and Space Administration Task Load Index (NASA-TLX). These "care components," alongside patient and environmental factors that influence workload ("modifiers"), will form the basis of the Standardized Workload Assessment Metric for Pediatric Emergency Departments (SWAMPED). We sought to obtain preliminary workload scores for each care component and assess the face validity of the NASA-TLX-derived workload tool.

The Research Agenda for Perinatal Innovation and Digital Health Project: Human-Centered Approach to Multipartner Research Agenda Codevelopment.

Background: Digital health innovations provide an opportunity to improve access to care, information, and quality of care during the perinatal period, a critical period of health for mothers and infants. However, research to develop perinatal digital health solutions needs to be informed by actual patient and health system needs in order to optimize implementation, adoption, and sustainability.

Objective: Our aim was to co-design a research agenda with defined research priorities that reflected health system realities and patient needs.

Caregiver and Youth Characteristics That Influence Trust in Digital Health Platforms in Pediatric Care: Mixed Methods Study.

Background: Combining patient-generated health data and digital health platforms may improve patient experience and population health, mitigate rising health care costs, reduce clinician burnout, and enable health equity. However, lack of trust may be a notable barrier to the data-sharing required by such platforms. Understanding sociodemographic, health, and personal characteristics will enable developers and implementers of such technologies to consider these in their technical design requirements.

Designing eHealth interventions for children with complex care needs requires continuous stakeholder collaboration and co-creation.

Objective: Hospital-to-home (H2H) transitions challenge families of children with medical complexity (CMC) and healthcare professionals (HCP). This study aimed to gain deeper insights into the H2H transition process and to work towards eHealth interventions for its improvement, by applying an iterative methodology involving both CMC families and HCP as end-users.

Methods: For 20-weeks, the Dutch Transitional Care Unit consortium collaborated with the Amsterdam University of Applied Sciences, HCP, and CMC families.

Prediction of Blood Risk Score in Diabetes Using Deep Neural Networks.

Improving the prediction of blood glucose concentration may improve the quality of life of people living with type 1 diabetes by enabling them to better manage their care. Given the anticipated benefits of such a prediction, numerous methods have been proposed. Rather than attempting to predict glucose concentration, a deep learning framework for prediction is proposed in which prediction is performed using a scale for hypo- and hyper-glycemia risk.

A Bridging Opportunities Work-frame to develop mobile applications for clinical decision making.

Background: Mobile applications (apps) providing clinical decision support (CDS) may show the greatest promise when created by and for frontline clinicians. Our aim was to create a generic model enabling healthcare providers to direct the development of CDS apps.

Methods: We combined Change Management with a three-tier information technology architecture to stimulate CDS app development.

eHealth: past and future perspectives.

eHealth is an umbrella term incorporating any area that combines healthcare and technology to improve efficiencies and reduce costs. The ultimate goal of eHealth is to rationalize treatment selection to improve patient safety and outcomes. Telemedicine, first used in the 1920s, is the oldest form of eHealth.

Fast and frugal trees: translating population-based pharmacogenomics to medication prioritization.

Aim: Fast and frugal decision trees (FFTs) can simplify clinical decision making by providing a heuristic approach to contextual guidance. We wanted to use FFTs for pharmacogenomic knowledge translation at point-of-care.

Materials & Methods: The Pharmacogenomics for Every Nation Initiative (PGENI), an international nonprofit organization, collects data on regional polymorphisms as a predictor of metabolism for individual drugs and dosages.

Personalized medicine policy challenges: measuring clinical utility at point of care.

Pharmacogenomics, driven by advances in genomics, helps to explain patients' individual variability in response to therapies. Personalized medicine, the application of the increasing understanding of pharmacogenomics, and information technology are intertwined from discovery to delivery at point of care, through to tracking clinical outcomes. Although exemplary cases of personalized medicine adoption demonstrate patient benefit and cost-effectiveness, a remaining barrier to large-scale real-world uptake of this novel approach in medicine is policy change.

Improving oncology outcomes through targeted therapeutics will require electronic delivery systems.

Typically, chemotherapy selection takes into account patient demographic data, including disease symptoms, family history, environmental factors and concurrent medications. Although validated and approved genomics tests are available for targeted therapeutics, a major challenge facing healthcare is the ability to process the genomic data in the patient's context and to return clinically interpretable dosing guidance to the physician in a realistic time frame. Delivery of these targeted therapeutics, made possible by clinical decision support systems connected to an electronic health record may help drive both the acceptance and adaptation of an electronic health record system, as well as provide personalized information at point-of-care, as part of the routine workflow.

Damming the genomic data flood using a comprehensive analysis and storage data structure.

Data generation, driven by rapid advances in genomic technologies, is fast outpacing our analysis capabilities. Faced with this flood of data, more hardware and software resources are added to accommodate data sets whose structure has not specifically been designed for analysis. This leads to unnecessarily lengthy processing times and excessive data handling and storage costs.

Integrating genomic-based clinical decision support into electronic health records.

There is a growing consensus that the first and most necessary step to improving the efficiency, cost-effectiveness and quality of healthcare systems can be achieved through the implementation of interoperable patient-centric electronic health record (EHR) systems across hospitals and clinics. Targeted therapeutics (including screening, prevention and disease management) through EHR-based clinical decision support delivery may drive both the acceptance and adoption of EHR systems by providing personalized information at the point-of-care. The realization of targeted therapeutics will depend on the resolution of current political, ethical, socioeconomical and technical challenges surrounding EHR implementation efforts.

Génome Québec & Montreal Heart Institute Pharmacogenomics Centre: a translational pharmacogenomics platform--from R&D to the clinic.

The Génome Québec and Montreal Heart Institute Pharmacogenomics Centre (Montreal, Canada), created in 2006, is a translational pharmacogenomics platform whose main objectives are to conduct pharmacogenomics research, provide pharmacogenomics services to the academic, biotechnology and pharmaceutical sectors, and integrate pharmacogenomics solutions into the healthcare system. The Centre has brought together a multidisciplinary team of researchers with expertise in genomics, bioinformatics and clinical trial research. All the Centre's clinical research studies are supported by the Centre's unique Good Laboratory Practice facility framework, which has the ability to perform pharmaceutical clinical trials and deliver clinical diagnostics under the highest standards.