The typical curriculum of training and educating future clinicians, biomedical engineers, health IT, and artificial intelligence experts lacks needed twenty first-century skills like problem-solving, stakeholder empathy, curiosity stimulation, entrepreneurship, and health economics, which are essential generators and are pre-requirements for creating intentional disruptive innovations. Moreover, the translation from research to a valuable and affordable product/process innovation is not formalized by the current teachings that focus on short-term rather than long-term developments, leading to inaccurate and incremental forecasting on the future of healthcare and longevity. The Stanford Biodesign approach of unmet clinical need detection would be an excellent starting methodology for health-related innovation work, although unfortunately not widely taught yet. We have developed a novel lecture titled HealthTec Innovation Design (HTID) offered in an interdisciplinary setup to medical students and biomedical engineers. It teaches a future-oriented view and the application and effects of exponential trends. We implemented a novel approach using the Purpose Launchpad meta-methodology combined with other innovation generation tools to define, experiment, and validate existing project ideas. As part of the process of defining the novel curriculum, we used experimentation methods, like a global science fiction event to create a comic book with Future Health stories and an Innovation Think Tank Certification Program of a large medical technology company that is focused on identifying future health opportunities. We conducted before and after surveys and concluded that the proposed initiatives were impactful in developing an innovative design thinking approach. Participants' awareness and enthusiasm were raised, including their willingness to implement taught skills, values, and methods in their working projects. We conclude that a new curriculum based on HTID is essential and needed to move the needle of healthcare activities from treating sickness to maintaining health.
Health longevity, cost reduction, prevention-based healthcare, personalized medicine, predictive diagnostic, transformed care delivery, de-aging, healthy lifestyle trends, and implementation of intelligent technologies should lead to a more democratized (availability for everyone on this planet) healthcare provision. Forecasting the future of healthcare and health policy certainly is imperfect but nevertheless a precious scientific approach that can lead to novel innovative approaches. In the last decade, the healthcare system faced several challenges, including the significant increase of care costs, demographic changes towards the older population, inability to prevent and overcome pandemics, increased chronic and non-communicable diseases, or resistance to adopting emerging technologies. The need to shift the focus from sickness to health becomes a critical mission. We developed a lecture titled "Healthtech Innovation Design" for graduate students from medicine, biomedical engineering, neuroscience and software engineering. The lecture's goal is to teach innovation methodologies, exponential technologies and methods to achieve healthcare democratization. A critical component is to promote initiatives with global teams focused on the future of health. The educational and initiative programs were impactful in growing interest toward innovation, focusing on disruption and healthcare democratization. Participants awareness towards the main issues and challenges was raised. Interdisciplinary participation was qualitatively processed to generate a holistic vision toward innovation. Through embracing digitalization to a patient-centric approach, affordable care services, and the expansion of precision medicine, the entire healthcare organization and management will likely undergo a worldwide change. Notably, digital technologies, the leverage of artificial intelligence and empathy would satisfy unmet clinical needs. With a future-oriented statement, the forecast of healthcare becomes more imaginable, in which democratization will allow the affordability of services in different countries and economic status.
Industry 4.0 and digital transformation will likely come with an era of changes for most manufacturers and tech industries, and even healthcare delivery will likely be affected. A few trends are already foreseeable such as an increased number of patients, advanced technologies, different health-related business models, increased costs, revised ethics, and regulatory procedures. Moreover, cybersecurity, digital invoices, price transparency, improving patient experience, management of big data, and the need for a revised education are challenges in response to digital transformation. Indeed, forward-looking innovation about exponential technologies and their effect on healthcare is now gaining momentum. Thus, we developed a framework, followed by an online survey, to investigate key areas, analyze and visualize future-oriented developments concerning technologies and innovative business models while attempting to translate visions into a strategy toward healthcare democratization. When forecasting the future of health in a short and long-term perspective, results showed that digital healthcare, data management, electronics, and sensors were the most common predictions, followed by artificial intelligence in clinical diagnostic and in which hospitals and homes would be the places of primary care. Shifting from a reactive to a proactive digital ecosystem, the focus on prevention, quality, and faster care accessibility are the novel value propositions toward democratization and digitalization of patient-centered services. Longevity will translate into increased neurodegenerative, chronic diseases, and mental illnesses, becoming severe issues for a future healthcare setup. Besides, data privacy, big data management, and novel regulatory procedures were considered as potential problems resulting from digital transformation. However, a revised education is needed to address these issues while preparing future health professionals. The “P4 of health”, a novel business model that is outcome-based oriented, awareness and acceptance of technologies to support public health, a different mindset that is proactive and future-oriented, and an interdisciplinary setting to merge clinical and technological advances would be key to a novel healthcare ecosystem. Lastly, based on the developed framework, we aim to conduct regular surveys to capture up-to-date technological trends, sustainable health-related business models, and interdependencies. The engagement of stakeholders through awareness and participation is the key to recognizing and improving healthcare needs and services.
Working memory performance can be influenced by motivational factors, which may be associated with specific brain activities, including suppression of alpha oscillations. We investigated whether providing individuals online feedback about their ongoing oscillations (EEG-neurofeedback) can improve working memory under high and low reward expectancies. We combined working memory training with neurofeedback to enhance alpha suppression in a monetary-rewarded delayed match-to-sample task for visual objects. Along with alpha, we considered the neighbouring theta and beta bands. In a double-blind experiment, individuals were trained over 5 days to suppress alpha power by receiving real-time neurofeedback or control neurofeedback (placebo) in Reward and No-Reward trials. We investigated (I) whether neurofeedback enhances alpha suppression, (II) whether monetary reward enhances alpha suppression and working memory, and (III) whether any performance benefits of neurofeedback-training would transfer to unrelated cognitive tasks. With the same experimental design, we conducted two studies with differing instructions given at the maintenance, yielding together 300 EEG recording sessions. In study I, participants were engaged in a mental calculation task during maintenance. In study II, they were instructed to visually rehearse the sample image. Results from study I demonstrated a significant training and reward-anticipation effect on working memory accuracy and reaction times over 5 days. Neurofeedback and reward anticipation showed effects on theta suppression but not on alpha suppression. Moreover, a cognitive training effect was observed on beta suppression. Thus, neurofeedback-training of alpha was unrelated to working memory performance. Study II replicated the training and reward-anticipation effect on working memory but without any effects of neurofeedback-training on oscillations or working memory. Neither study showed transfer effects of either working memory or neurofeedback-training. A linear mixed-effect model analysis of neurofeedback-independent training-related improvement of working memory combining both studies showed that improved working memory performance was related to oscillatory changes over training days in the encoding and maintenance phases. Improvements in accuracy were related to increasing beta amplitude in reward trials over right parietal electrodes. Improvements in reaction times were related to increases in right parietal theta amplitude during encoding and increased right parietal and decreased left parietal beta amplitudes during maintenance. Thus, while our study provided no evidence that neurofeedback targeting alpha improved the efficacy of working memory training or evidence for transfer, it showed a relationship between training-related changes in parietal beta oscillations during encoding and improvements in accuracy. Right parietal beta oscillations could be an intervention target for improving working memory accuracy.
With the advent of the fourth industrial revolution accompanied by the Internet of Things, the implementation of smart technologies and digitalization already had a great impact in our society, especially when considering exponential innovation and human development. In this context, some types of employment have already been replaced or have been enhanced by the use of robots, human-machines interfaces and Artificial Intelligence systems. And there is likely more to come. If innovation can be viewed as a direct or indirect outcome of scientific research, which role will a scientist play in 2035? We developed a survey to investigate the opinions of scientists with respect to the possible future implementation of disruptive technologies, their feelings and approaches to digitalization, and particularly the impact of digital transformation on scientific education. In a futuristic scenario, we can imagine that scientists will be supported by technologies, carrying out numerous experiments, managing big datasets, producing accurate results, increasing communication, openness and collaboration among the worldwide scientific community, where ethics, regulations and social norms will always be observed. The new era of Digital Science is coming, in which humans will start to incorporate more disruptive and advanced technologies into their daily life; essential aspects for exponential innovation and development.
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