2.7 EMR/EHR as a Future Platform for a Co-Creation
Innovation Model?
Clinical data are more than information, and clinical data management at the
fingertips of medical professionals drives efficiency and better patient management.
Clinically, the next level of integration will drive the development of clinical
decision systems targeting a more disease focus through evidence-based medicine
including the usage of semantic reasoning engines looking at large databases and the
natural language processing capabilities (NLP) transforming unstructured data into
structured data. The purpose is to deliver smart, accessible clinically relevant data at
the fingertips of the clinicians in various medical areas such as cardiology and
oncology. For instance, clinicians will benefit from a “system that automatically
get the right relevant information” through context-aware capabilities. This
advanced clinical decision support will include clinical pathway management “on
the fly,” aiming to cover descriptive and predictive analytics for medical
professional.
On the front of the mobility of data, IT technology firms aim to develop new
solutions that enable clinicians to focus on their patients, while sharing data across
the enterprise. Going beyond the outpatient management, they aim to support the
integrated care approach by designing healthcare IT platforms connecting acute care,
ambulatory care, and overall care providers. This area of innovation will leverage IT
technology components such as cloud deployment and Internet of Things (IoT).
EMRs and EHRs should provide clinicians and patients with all the information
they need at the right time, meaning that the IT solution will prepare and present the
information easily to be used and digested by the medical professionals. Clinical
users expect that IT firms will enrich this information with clinical intelligence and
decision support tools, empowering all the different caregivers to make fast and
confident diagnosis while actively participating to treatment decisions. This will
significantly contribute to the goal of precise medicine, supported by artificial
intelligence (AI).
2.8 AI in Healthcare Focusing on People, Not on Pure
Technology
Rapid advances in technology are enabling the capture of more data than ever before
about the human body and people’s lifestyles, about diseases and their treatments,
and about the hospitals and health systems that care for individuals and populations
around the globe. However, empirical evidence shows that only a fraction of this
data is used effectively to improve the quality and efficiency of care, and to empower
people to take control of their own health.
More data do not equal more insight. On the contrary, it can be a burden to
people. Consumers with health trackers often do not know what to do with the
118
J. Galbrun
Innovation Model?
Clinical data are more than information, and clinical data management at the
fingertips of medical professionals drives efficiency and better patient management.
Clinically, the next level of integration will drive the development of clinical
decision systems targeting a more disease focus through evidence-based medicine
including the usage of semantic reasoning engines looking at large databases and the
natural language processing capabilities (NLP) transforming unstructured data into
structured data. The purpose is to deliver smart, accessible clinically relevant data at
the fingertips of the clinicians in various medical areas such as cardiology and
oncology. For instance, clinicians will benefit from a “system that automatically
get the right relevant information” through context-aware capabilities. This
advanced clinical decision support will include clinical pathway management “on
the fly,” aiming to cover descriptive and predictive analytics for medical
professional.
On the front of the mobility of data, IT technology firms aim to develop new
solutions that enable clinicians to focus on their patients, while sharing data across
the enterprise. Going beyond the outpatient management, they aim to support the
integrated care approach by designing healthcare IT platforms connecting acute care,
ambulatory care, and overall care providers. This area of innovation will leverage IT
technology components such as cloud deployment and Internet of Things (IoT).
EMRs and EHRs should provide clinicians and patients with all the information
they need at the right time, meaning that the IT solution will prepare and present the
information easily to be used and digested by the medical professionals. Clinical
users expect that IT firms will enrich this information with clinical intelligence and
decision support tools, empowering all the different caregivers to make fast and
confident diagnosis while actively participating to treatment decisions. This will
significantly contribute to the goal of precise medicine, supported by artificial
intelligence (AI).
2.8 AI in Healthcare Focusing on People, Not on Pure
Technology
Rapid advances in technology are enabling the capture of more data than ever before
about the human body and people’s lifestyles, about diseases and their treatments,
and about the hospitals and health systems that care for individuals and populations
around the globe. However, empirical evidence shows that only a fraction of this
data is used effectively to improve the quality and efficiency of care, and to empower
people to take control of their own health.
More data do not equal more insight. On the contrary, it can be a burden to
people. Consumers with health trackers often do not know what to do with the
118
J. Galbrun