Both artificial intelligence and augmented
intelligence share the same goal but have different approaches to achieve it.
As providers strive to improve patient outcomes,
the use of machine learning has become more integrated into the healthcare
system. As this new form of technology continues to expand, it’s important to
understand how it can be used and how it differs from augmented intelligence.
While the phrases artificial intelligence
and augmented intelligence are often used interchangeably in healthcare,
defining both terms creates specific usages for the machine learning systems in
the industry. Artificial intelligence and augmented intelligence share the same
objective but have differing procedures in accomplishing it.
Although both techniques use machine
learning capabilities, artificial intelligence takes a full device approach,
while augmented intelligence maintains the human aspect.
COMPARING ARTIFICIAL AND AUGMENTED
INTELLIGENCE
Especially in recent years, the healthcare
industry has done extensive research on how to use artificial intelligence to
improve patient outcomes. However, augmented intelligence options have been
less explored.
Augmented intelligence is like artificial
intelligence in the way they both use machine learning to enhance care quality.
However, instead of replacing human intelligence, augmented intelligence works
to build upon it.
While artificial intelligence and augmented
intelligence both have a shared goal of improving a patient’s quality of care
and outcomes, these machine learning techniques have different methods to
achieve the desired results.
AUGMENTED INTELLIGENCE IN HEALTHCARE
Augmented intelligence, also known as
intelligence amplification, cognitive augmentation, decision support, machine
augmented intelligence, and enhanced intelligence, plays a similar role as
artificial intelligence. However, augmented intelligence keeps human
intelligence elements in its procedure.
Rather than performing the assignment for a
physician like in the case of artificial intelligence, augmented intelligence
acts as a tool to assist the physician in the task.
Augmented intelligence can be particularly
helpful in the field of medical imaging. According to a HIMSS whitepaper by
AGFA Healthcare, augmented intelligence can improve workflows, assist in
speeding up the diagnosis process, and pave the way for personalized medicine.
“In my group, we’ve
already demonstrated that an AI [augmented intelligence] system for chest x-ray
triaging and prioritization can lead to much faster reporting turn around time.
We’ve also shown potential diagnostic benefits in early detection of lung
cancer,” Professor of Data Science at Warwick University, Giovanni Montana,
said in the whitepaper.
While augmented intelligence allows for a
collaborative approach between machines and physicians, it doesn’t lighten the
load for physicians as much as artificial intelligence. Rather than having to
sort through electronic health records or large data sets, physicians can just
focus on delivering quality care to their patients. Rather, augmented
intelligence should work with clinicians to provide the best quality of care
for the patient.
ARTIFICIAL INTELLIGENCE IN HEALTHCARE
Artificial intelligence has transformed the
healthcare industry and how patients receive care. By analyzing large data
sets, providers can quickly pull information to deliver the best possible care
to their patients.
Data will often be scatted across different
systems, causing an issue in data management. Artificial intelligence
technology sorts through data, improving accessibility and efficiency.
Recently, Health Center Partners (HCP)
launched a collaborative effort with Arcadia to better manage data and address
health disparities. Arcadia assisted in the creation of a master patient index
to detect potential gaps in care.
“You can see which patients have true
quality gaps, and that’s where we would act on that data, and healthcare
providers would reach out and make sure that the patient has all of their
quality measure interventions and gaps closed,” Sarah Cho, vice president of
clinical transformation and health informatics for Integrated Health Partners,
a subsidiary of HCP told HealthITAnalytics.
With the master patient index, the tool can
take all patient data and put it into a shared data asset that is used across
all of HCP’s member health centers. According to Amanda Simmons, executive vice
president for Integrated Health Partners, this creates a “no wrong door
policy.”
Patients have access to 81 clinical sites
through the network and will not get turned away if they go to a center that’s
not their primary care provider. Arcadia then gives the network the tool to see
longitudinal records and the patient’s activity across all the health centers.
While artificial intelligence has proven to
create positive outcomes in the health realm, some argue that artificial
intelligence relies too much on the machine’s ability to assess data and
provide treatment plans. Because of the sensitivity of the healthcare industry,
human intelligence cannot be replaced, some skeptics say.
While artificial intelligence and augmented
intelligence offer different solutions to improve patient outcomes, both are
effective methods in enhancing the quality of care and creating a more
technology-based healthcare system.
