numbers they are given. With current EMR solutions, clinicians spend more time
with machines than face to face with their patients. Additionally, providers are
drowning in data but lacking in insights to drive improvements that matter to their
patients, staff, and eventually the bottom line for hospitals and clinics. This is where
artificial intelligence (AI) can help.
Thanks to advances in computing power as well as inroads in data science, AI
methods like machine learning and deep learning are arriving into the mainstream.
They can help to make sense of large amounts of data, turning it into actionable
insights. However, in healthcare, which is arguably more complex than any other
industry, and where lives are at stake, applying AI in a beneficial and responsible
way requires more than just heavy number crunching. It also requires an intimate
understanding of the personal, clinical, or operational context in which it is used. At
the same time, we need to be sensitive to the fact that there is a relentless demand on
people—professionals, patients, and consumers alike—to keep adapting to new
technology. AI-enabled solutions should make things easier for them, not more
complicated.
In medical settings, artificial intelligence combines the power of AI with human
domain knowledge to create solutions that adapt to people’s needs and environments—helping people to live healthy lifestyles and helping healthcare providers to
achieve the quadruple aim of improving patient experiences and the work–life of
care providers, alongside improved health outcomes for a lower cost of care.
Artificial intelligence augments people, rather than replacing them. It acts like a
personal assistant that can learn and adapt to the skills and preferences of the person
that uses it, and to the situation he or she is in. The technology does not call attention
to itself, but runs in the background—deeply integrated into the interfaces and
workflows of hospitals, and almost invisibly embedded into solutions for the consumer environment. More and more actors from doctors to firms are shaping a reality
today that will become available in the near future from these various research
applications.
Firms closely work with clinical partners across the globe—healthcare providers,
academia, and hospital networks—to develop AI-enabled solutions that are secure,
firmly grounded in scientific research, and rigorously validated in clinical practice:
• Solutions like wearable vital sign sensors with intelligent software that help a
hospital to monitor large numbers of patients so that doctors could spot emerging
risks.
• Other example, the application that uses algorithms derived from psychological
theories of behavior change to help motivate people to stick to their sleep therapy
treatments for longer.
• We foresee the development of intelligent dashboards that combine data from
various sources, turning them into relevant information that clinicians need to
help reduce their cognitive load.
Health Informatics and Co-Innovation: Connecting Patients, Clinical Practice,. . .
119
with machines than face to face with their patients. Additionally, providers are
drowning in data but lacking in insights to drive improvements that matter to their
patients, staff, and eventually the bottom line for hospitals and clinics. This is where
artificial intelligence (AI) can help.
Thanks to advances in computing power as well as inroads in data science, AI
methods like machine learning and deep learning are arriving into the mainstream.
They can help to make sense of large amounts of data, turning it into actionable
insights. However, in healthcare, which is arguably more complex than any other
industry, and where lives are at stake, applying AI in a beneficial and responsible
way requires more than just heavy number crunching. It also requires an intimate
understanding of the personal, clinical, or operational context in which it is used. At
the same time, we need to be sensitive to the fact that there is a relentless demand on
people—professionals, patients, and consumers alike—to keep adapting to new
technology. AI-enabled solutions should make things easier for them, not more
complicated.
In medical settings, artificial intelligence combines the power of AI with human
domain knowledge to create solutions that adapt to people’s needs and environments—helping people to live healthy lifestyles and helping healthcare providers to
achieve the quadruple aim of improving patient experiences and the work–life of
care providers, alongside improved health outcomes for a lower cost of care.
Artificial intelligence augments people, rather than replacing them. It acts like a
personal assistant that can learn and adapt to the skills and preferences of the person
that uses it, and to the situation he or she is in. The technology does not call attention
to itself, but runs in the background—deeply integrated into the interfaces and
workflows of hospitals, and almost invisibly embedded into solutions for the consumer environment. More and more actors from doctors to firms are shaping a reality
today that will become available in the near future from these various research
applications.
Firms closely work with clinical partners across the globe—healthcare providers,
academia, and hospital networks—to develop AI-enabled solutions that are secure,
firmly grounded in scientific research, and rigorously validated in clinical practice:
• Solutions like wearable vital sign sensors with intelligent software that help a
hospital to monitor large numbers of patients so that doctors could spot emerging
risks.
• Other example, the application that uses algorithms derived from psychological
theories of behavior change to help motivate people to stick to their sleep therapy
treatments for longer.
• We foresee the development of intelligent dashboards that combine data from
various sources, turning them into relevant information that clinicians need to
help reduce their cognitive load.
Health Informatics and Co-Innovation: Connecting Patients, Clinical Practice,. . .
119