What is AI in healthcare?
Discover how artificial intelligence (AI) is influencing the world of
healthcare. We explore the pros and cons of AI, current applications, and what
the future holds.
AI in healthcare is getting more sophisticated and efficient at
supporting doctors and other medical professionals. Not only does this provide
a real opportunity for growth within the profession, but it also means that
tasks can be completed more quickly and at a lower cost.
The potential for AI in healthcare is huge, as it has the ability to
apply problem-solving techniques that humans could not do alone. In 2019, 46% of healthcare organisations in the UK
were using AI technology, which indicates how widely it is already used.
With no signs of slowing down, the growth of AI in healthcare is a trend
worth recognising and familiarising yourself with. In this article, we’ll
explore how AI affects healthcare, the pros and cons, and current applications.
We’ll also take a look at what the future may hold for artificial intelligence
in healthcare.
How does AI affect medicine and healthcare?
The impact of AI in medicine and healthcare has been enormous and
continues to grow exponentially. Put simply, AI describes computers and similar
machines that replicate human cognition and are therefore able to learn, think
(in a sense), and make decisions on our behalf.
When you apply this to healthcare, some of the outcomes include:
- Machine
learning is used to analyse medical data and reveal insights. These
insights are then used to improve patient experiences and health outcomes.
- AI
supports medical professionals, both in conducting research and in
clinical settings. For example, AI may help medical professionals make key
decisions about medications and treatments by accessing research relevant
to the procedure and the patient’s needs.
- Medical
imaging, where scans and X-rays are analysed in order to eliminate the
risk of human error.
- AI
makes healthcare more predictive and proactive by analysing data to
improve preventive care recommendations.
AI and
healthcare: How things look currently
In many cases, the role of AI in healthcare is still at a fairly embryonic
stage. Therefore, research and results from its use are still being gathered
and analysed in order to make improvements and revolutionise the way healthcare
is distributed in the UK and around the world.
However, at this stage, it’s clear to see the
huge amount of opportunity that’s available to the profession by embracing AI.
Researchers, clinicians, and patients are already reaping the benefits of its
introduction, which will inevitably lead to a rapid roll-out of new
technologies in the near future.
If the current growing trend of AI use in
healthcare continues, it’s clear that it will become a core part of future digital health systems, helping to
revolutionise medicine and healthcare to the benefit of anyone that interacts
with it.
This matters because good healthcare is at the
heart of a thriving society, so having the ability to analyse data in a more
efficient and productive way is hugely important.
It could easily be the difference between life
and death, enhancing patient care and improving the overall
quality of life for the human race.
As seen recently with the COVID-19 pandemic, it
could also be instrumental in helping to prevent and combat pandemics.
Pros
and cons of AI in healthcare
In order to better understand the role of AI in
healthcare, it’s good practice to familiarise yourself with the pros and cons
of using it in the profession.
Advantages of AI in healthcare
1. Ability to analyse data and improve
diagnosis
When it comes to medical records and other
healthcare-related data, AI technology is able to analyse it much faster than
humans are able to, and often more accurately. This can help medical
professionals reach a diagnosis a lot more quickly and allow
them to perform their duties more effectively.
2. Better patient care
If implemented correctly, AI in healthcare
should improve the patient care that’s offered.
It achieves this by cutting down on research
time, facilitating the better use of resources, and reducing errors.
Integrating medical AI into clinician workflows
can also give healthcare professionals valuable context while they’re making
important decisions about treatments.
3. Reduced cost of care
There are plenty of ways AI can reduce costs,
both financially and time-wise. Machine learning in healthcare can ease the
burden of time-consuming administrative tasks, reduce medical errors, and
complete tasks a lot more quickly than a human may be able to.
4. Real-time, accurate data
When it comes to medical issues, it’s
incredibly important to offer a diagnosis as quickly as possible. To do this,
it’s vital that medical professionals receive accurate data that allows them to
make critical decisions more effectively.
Real-time data reduces costs, minimises waiting
times, and offers a greater chance of being able to prevent a condition from
worsening.
5. Improved workload and reduced staff
stress
It’s no secret that jobs in healthcare can be
incredibly stressful, and quite often departments find themselves
short-staffed. Artificial intelligence in healthcare could help to address this
issue, taking on some of the workloads to help ease the burden.
Busy schedules and personal stress can also
impact the standard of care provided, which is another reason why staff mental health is so important.
6. Support with administrative
tasks
Saving time on administrative tasks means
medical professionals can place more focus on patient care and other important
areas of their job. Tasks AI can help with include maintaining records, scan
analysis and data entry.
7. Health monitoring and digital
consultations
Whether it’s wearable technologies that
help monitor a patient’s health or digital consultations that can be done on a
smart device, AI is a great way of improving the way medical professionals
record and analyses data. It also allows patients to monitor their own health
and receive expert assistance online.
Disadvantages of AI in
healthcare
1. Training
complications
Not only do medical
professionals need to receive extensive training to use a lot of AI
technologies, but the AI tools themselves also need to be trained with curated
data in order to perform properly. In both cases, this can lead to
complications that wouldn’t exist without the introduction of AI.
2. Risk of creating
unemployment
The robots are coming! In the past, it was often
joked that robots would take over the world and steal our
jobs, but AI and automation do actually pose a very real threat to a lot of
sectors. Healthcare is no different, where the introduction of AI could mean
that a lot of administrative roles are made redundant.
3. Too much change
can be difficult to manage
No matter the industry,
too much change can be incredibly disruptive. That’s why it’s important to
strike a balance and ensure departments are ready for AI before it’s rolled
out.
This is particularly
important in healthcare, where key decisions can quite literally be the
difference between life and death. The healthcare sector needs to be sure that
AI can be used effectively and that all staff understand how medical technology works.
4. Still requires
human input
AI has come on leaps
and bounds in healthcare, but human input and surveillance are still relied
upon. Humans are unique in the sense that they can notice behavioural
observations and empathise with patients in a way that no machine can.
Sometimes, these
observations can be pivotal in a medical diagnosis and prevent further
complications.
5. Increased security
risk
AI systems can be
vulnerable to security risks, which poses a massive problem to the healthcare
industry, as patient data needs to be kept confidential.
Cyber attacks are becoming more sophisticated
and accurate, while also proving harder to predict and prevent. This means that
healthcare institutions will need to invest an awful lot of money to ensure
they keep cybercriminals at bay.
6. Social variables
may not be considered
When treating patients,
it’s often not just about physical conditions. In fact, social, historical, and
economic factors can also influence the specific care an individual
needs.
While AI is more than
capable of allocating treatment based on the diagnosis, it isn’t yet capable of
considering other social variables that may influence a medical professional’s
decision.
7. Inaccuracies could
occur
Using AI in medicine
would eradicate a lot of human-based errors, but it wouldn’t be able to get rid
of inaccuracies completely.
Whenever there is a
huge amount of data involved, mistakes are still likely to occur, and data gaps
can also be an issue. This could have potentially serious consequences in areas
like medicine prescription.
Applications of AI in
healthcare
There are plenty of instances where artificial intelligence is already being used in
healthcare successfully, as well as countless opportunities for its involvement
in the future. Here, we will take a look at some of the ways in which AI could
have a positive impact on the profession.
Illness detection and diagnosis
Machine learning in healthcare could be used to
detect more complex conditions that aren’t immediately apparent when someone
receives a diagnosis. It could also be used to monitor patients to see when
conditions worsen. The AI technology would then be able to collect vital data
and alert medical professionals.
Medical imaging
AI is already being used in medical
imaging, following research that suggested AI could be as effective
at detecting diseases, such as cancer, as human radiologists.
Not only is this vital for early prevention but
also means that medical images can be examined a lot more quickly and
thoroughly with the help of AI – eliminating the risk of human error.
Drug creation and development
AI in medicine can be used to create new drugs
by analysing data and already existing medicines. Discovering and developing
medicine is incredibly costly and time-consuming. With the help of AI, costs
could be reduced and promising new drugs could be found much faster.
Managing medical records
As we have already discussed, AI could be an
instrumental tool in collecting and analysing data, such as medical records.
Not only does this help medical professionals to work a lot more effectively,
but it also means they can work faster and prioritise other important aspects
of their job.
Improving access to care
Medical professionals are always in demand and
quite often there are staff shortages. In developing countries, this becomes
even more of an issue. By using AI, life-saving care can be more readily
available to people all over the world and be used to fill skills gaps and help
with diagnosing patients.
Monitoring health using wearables and
personal devices
Wearables are already being used in healthcare
to monitor patients and smart devices to conduct digital consultations.
The use of these technologies is only likely to
increase, allowing medical professionals to intervene at the first sign of
problems and ensure patients receive treatment and care as soon as possible.
What
is the future of healthcare?
Despite there being both positives and
negatives associated with artificial intelligence in healthcare, it’s clear
that in the main it’s seen as a force for good and will continue to be
developed and used more widely moving forward.
In fact, it already plays a pivotal role in
understanding the needs of patients through in-depth data analysis. Medical
professionals are likely to rely on it even more for guidance and support,
using it effectively to provide accurate and timely treatment to
patients.
Ultimately, the role of AI in medicine is to
eliminate human error, make the lives of hard-working medical professionals
easier, and improve the way care is delivered.
Whether you work in the medical profession or
find yourself requiring treatment in the future, it’s likely that seeing AI
technology used within a healthcare environment will become very normal.
AI
in healthcare: additional courses
Hopefully, thanks to our guide, you now feel
better informed about the role of AI in healthcare, now and in the future.
While it may seem like a very complex topic on the surface, it’s undoubtedly
something we should all familiarise ourselves with, as it’s likely to impact
the way we receive care in the very near future (if it hasn’t already).
If you’d like to further your understanding and explore some of the key themes we have discussed in more detail, then why not take a look at some of the courses we offer here at FutureLearn?