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As patients strive to manage their own health and illnesses, many wonder how to get a copy of their health data to share with their physicians, load into apps, donate to researchers, link to their genomic data, or have on hand just in case. To...
The All of Us Research Program is a historic effort to gather data over many years from one million or more people living in the United States, with the ultimate goal of accelerating research and improving health.
Unlike research studies that are focused on...
When is it appropriate to return individual research results to participants? The immense interest in this question has been fostered by the growing movement toward greater transparency and participant engagement in the research enterprise. Yet, the risks of returning individual research results—such as results with...
This report develops both backward- and forward-looking analyses of the impacts of automation over the years 1980 to 2016 and 2016 to 2030 across some 800 occupations. In doing so, it assesses past and coming trends, and suggests a comprehensive response framework for national and state-local policymakers.
A publicly accessible report from the 2018 Digital Health Consumer Adoption survey, conducted by Rock Health. The survey consists of 4,000 respondents of US adults aged 18 and over.
The World Economic Forum’s system initiative “Shaping the Future of Health and Healthcare” aims to provide answers to the question: How can the world deliver affordable and quality healthcare for nearly 9.7 billion people by 2050?
Researchers are calling for greater regulation and transparency as analysis of medicines-related apps found most directly shared user data - including sensitive health data - with third parties, posing an unprecedented privacy risk.
Hospitals are exploring new uses in intensive care units and surgical recovery rooms, and contemplating a future in which Alexa, or another voice avatar, becomes a virtual member of the medical team.
What are the obstacles that inhibit data-sharing and how can we move from this paradox, which inhibits the promise of precision medicine, to a policy for action all can accept?
Artificial intelligence (AI)- and machine learning (ML)-based technologies have the potential to transform healthcare by deriving new and important insights from the vast amount of data generated during the delivery of healthcare every day. Example high-value applications include earlier disease detection, more accurate diagnosis, identification...