Artificial Intelligence in Healthcare Utilization Presentation 2022

Name
Institutional Affiliation
ARTIFICIAL INTELLIGENCE IN HEALTHCARE

Introduction
 Artificial intelligence is the use of complex and complicated
algorithms to emulate human operations. Human cognition is
analyzed by machines and they are emulated specifically by
these machines. In health care computer algorithms the
computers are programmed to assimilate human brains. AI
creates the ability of the machines and the computers to carry
out decisions and technicalities without the help of direct
human input. Artificial intelligence has the capability of
processing raw data into information that can be defined and
be relayed to the end user. What places AI different from the
rest of the technologies is that it is able to recognize patterns in
human behavior and adapt them. Apart from adapting human
behavior artificial intelligence also has the capability of using
logic to define what they should do. However, there is a margin
of error on the dependency of artificial intelligence.

Why should health care managers be aware of artificial
intelligence?
 Health care utilization
 Increasing patient satisfaction
 Optimizing staff levels of efficiency

Health care utilization
 Health care utilization is one area which forces health care
managers to keep in trend with artificial intelligence. In
definition health care utilization is the use of health care
services in a manner that it provides help to the public. It is the
health care services on people and the public from different
agencies for the purposes of preventing, curing and promoting
maintenances of health and well being of the health statuses of
different persons who need it the most (Dean, Moss, McCarthy,
& Armstrong,2017).
 Utilization of health care is actualized in many different ways.
Prevention and cure is one way through which health care
utilization is actualized. Other forms of health care utilization
include; obtaining information from the public about health
status, conducting levels of prognosis of different infection and
analyzing disease data at different levels.

Artificial intelligence
 Healthcare

Health utilization
 Firstly through artificial intelligence new and improved drugs have been
formulated. These new and improved drugs can easily be disseminated with the
help of artificial intelligence. A perfect example of improved drugs is anesthesia
and analgesia. The improvement of anesthesia and analgesia has subsequently led
to the growth of ambulatory surgery. Surgery has been made easier through
adopting less invasive ways that the previous non-treatable pains and surgeries.
New drugs have been invented through the actualization of artificial intelligence
which has the ability to lengthen the course of the disease and cure at times at
increased cost but very worth it (Dunn, Moore, Miao, Kirsner, & Koru‐Sengul, 2018).
 Combinations of artificial intelligence have been so effective to the extent some
drugs are used to manage more than one infection. HIV/AIDS and cancer have
been managed efficiently through artificial intelligence (Jiang et al.,2017) Artificial
intelligence has enabled a combination of chemotherapy for many types of cancer
to be managed against other life style conditions like diabetes. Through artificial
intelligence forms of machine learning have now been combined. A perfect
example is scanning machines which have been combined using artificial
intelligence so that the same machine handling scanning is the same one that
handles technical things like combined positron emission, X-rays, computed
tomography, positron emission tomography and magnetic resonance imaging.

Health care utilization
 Artificial intelligence has made it easier for the mentioned health care
resources to reach a huge number of the public. Medical equipments
have been reduced through artificial intelligence in ways they are easier
to use and transport. The easier transportation makes it easier for the
health care managers to transport them to different places at they get
ways in which men can be helped. Complex forms of treatment through
the help of artificial intelligence can leave hospital premises and reach
places where they are essentially needed like homes and houses.
 Since the average length of hospitalizations is decreased through the
help of artificial intelligence, health care managers should think about
artificial intelligence as a way of providing health care utilization to the
public (Lee et al., 2020). From the advantages of artificial intelligence
mentioned above it is clear that health care utilization has been made
efficient and easier. It is the role of health care manager to be aware of
trends in artificial intelligence which will help in the bettering of health
care services and utilization to the people.

Patient satisfaction
 Health care managers should be concerned about patient satisfaction.
Patient satisfaction is only achievable through quality provision of health
care services. Quality of care involves obtaining the required service
and the availability of accessing the care. Health care organizations and
managers have continued to push for the satisfaction of patient
experience in most health care facilities. Patients for the longest time
have complained of poor cancer care quality since health care
organizations are strapped for time and limited to quality care.
 Health care organizations only depend on providers who limit quality at
the expense of pay. Out of the concern for quality, health care managers
should think about artificial intelligence. Artificial intelligence has the
capability of performing cancer screening for many patients within a
limited time without the help of any human. Primary health care
providers might not be at a position to provide care, but development of
artificial intelligence might just be the solution needed.

Patient satisfaction
 Additionally, patient navigators always remained
an intelligent way of sifting through patient
pathology. However, the method has been
inefficient and a concern to most health care
organizations and managers. The pathological
reports of most patients were not pathologically
expert provided.
 Health care managers thinking through finding a
solution have to consider artificial intelligence
which definitely provides for an efficient process
dictated by expert opinion and professional
analysis.

Optimizing staff level of efficiency
 Health care as an industry suffers from human resource crisis.
There are not enough health personnel in the country, starting
from registered nurses to medical physicians. The human
resource crisis is widening worldwide. From the obvious
analysis, it is impossible to provide patient care efficiently
without proper care. A lot of patients receive half baked care
or no care at all due to limited persons with the technique to
care of them.
 The human gap can only be filled through finding a
technological option. The best trend that can fill the gap of
human resources crisis experienced in health care industry is
artificial intelligence. Health care managers should think
about using artificial intelligence since it has the capability of
facilitating diagnostics and influencing decision making just
like professional humans do

The impact of artificial intelligence to
stakeholders in Florida Cancer Centre
 Mid Florida Cancer care has
confessed of using artificial
intelligence and with it a lot has
changed or bound to change within
the hospital if they have not changed
yet. The experience of everyone has
changed from the stakeholder;
administrators to patients have
changed in ways that have been
discussed below;

Management and
administration
 Running a cancer hospital has always been something of a logistical
nightmare. It is also important to note that in America the number of
cancer patients from the state, the country and the globe have made it
almost impossible to get bed space, there is poor visibility and increased
waiting times.
 The adoption of artificial intelligence would mean a lot for administrators
and management of Mid Florida Cancer Centre (Maddox, Rumsfeld, &
Payne, 2019). The Centre has adopted Artificial Intelligence powered
analytics platforms that use machine learning as a technique. For the
management and administrators their work has been made a little simpler.
 The machine is able to predict the emergency rate of a patient to be given
a bed space or not. The machine has, therefore, reduced the work load for
the managers having to decide which patients require bed spaces more
than the others. The predictive capability of the machines has made it very
accurate to approximate the duration within which each of the patients will
require the bed space. For administrators work has just become easier
than ever before.

Doctors and adoption of AI in Mid Florida Cancer Centre
 Apart from administrators and managers the adoption of technology has influenced changes
in the operations of doctors and physicians who operate in the cancer centre. The first impact
is that AI has outperformed the doctors diagnosing performance. Artificial intelligence is more
accurate than doctors in diagnosing cancer from mammograms. Researchers from Google
Health and Imperial College London visited the Cancer centre recently and conducted
research about breast cancer and the ability of doctors reading cancer from the
mammograms.
 A total of 29000 women were tested of breast cancer. At the end of the research, there was a
clear indication that the artificial intelligence algorithm out performed six radiologist in
reading the mammograms. The radiologists had predicted that over 10000 women were not
affected by cancer.
 Out of those the AI detected approximately 4000 that the doctors had predicted wrongly. The
research concluded that AI was as good as two doctors working together. For doctors in the
cancer centre AI is good since it provides accurate results for them to use. Additionally, AI has
provided doctors within the centre with more resting time. Unlike human doctors in the
hospital AI is tireless. The doctors in the hospitals used to tire and at times doze while on duty.
Fatigue could make the management deal with a lot of doctors’ cases of depression. However,
AI is tireless; it has improved cancer detection and accuracy in treatment. The doctors are
capable of affording enough rest time thereby limiting cases of fatigue and depression.

Nurses affected by adoption of artificial intelligence in the
cancer centre
 Apart from administrators, managers, doctors, physicians and
radiologists adoption of artificial intelligence has also affected
nurses in different ways. There are three main ways in which
nursing analytics in the cancer centre has been improved.
 AI has improved recovery planning for the nurses onto their
patients. AI has made it easy for the nurses to analyze disease
progression, health risk protection and virtual assistant. Nurses
have been given the ability to accurately help the cancer patient
with precision that comes from adoption of AI.
 Nurses in the cancer centre have also alluded that AI has been
significant in disease management. Patient data collected from
doctors combined with academic evidence from AI assist the
nurses to get the required medical images and personalize
treatment plans for each of the cancer patients.

Patient benefit of AI at the Mid Florida Cancer Centre
 The main groups of people who have felt
the impact of AI are the cancer patients.
The cancer patients are treated with
dignity, efficiency, accuracy and lesser
time all thanks to the invention of AI in
the cancer center. Patients now have
access to quality health care and quality
health care systems something that
would not be possible without the
implementation of AI in cancer centers.

Challenges and Possibilities faced in applying Artificial
intelligence
 The management of cancer using AI has not been easy for the cancer
centre. One of the major opportunities that the management of the Mid
Florida Cancer centre noticed through the full implementation of AI is the
increased number of cancer patient admissions. The facility was able
increase their capability of handling cancer patients from the states and
even abroad. The second opportunity was presented to the doctors,
physicians and radiologists are that it magnifies opportunities at the rate of
14 times above normal rate. In terms of business operations the
management predicted a 40% increase in profit.
 40% increase in profits is exceptionally huge and makes the center an
enterprise (Yu, Beam, & Kohane, 2018). The managers projected an
opportunity of 16% automation. The labs used in the medical centre are in
current times accessible to other professionals’ world over thanks to
artificial intelligence. Artificial intelligence is not confined to their
innovative laboratories the managers predicted an opportunity for the
centre to share researches among each other. With the shared information
an opportunity of amazing potential of innovation in the medical centre can
be realized.

Challenges and Possibilities faced
in applying Artificial intelligence
 The management of Mid Florida centre took chances with
the opportunities that investing in artificial intelligence had
presented. The journey, however, has not been easy the
centre has received a number of challenges. The first
challenge is that AI utilized a lot of processing power. The
processing power made it extremely difficult for the
managers to acquire artificial intelligence.
 AI has been in discussion and there has never been enough
power to process the machinery. The processing power
challenge influenced the managers at Mid Florida Cancer
Center to deal with a lot of logistic issues. A second
challenge apart from the processing power plant is the
adoption. The Mid Florida Cancer Centre was fully
operational before the adoption of Artificial Intelligence.

Challenges and Possibilities faced
in applying Artificial intelligence
 The system of the hospital was fully
operational. The plan always seemed
good in paper, but putting it to practice
was not only challenging to the
managers but also the doctors and the
nurses. To overcome the challenge of
adoption the management had to
organize training programs amongst its
medical members.

Challenges
 The move was quite expensive since
it involved fetching trainers from
external organizations to train local
staff but it was worth every move.
Lastly the persons experienced
challenges in developing AI
algorithms.

Challenges
 Every system of AI has unique codes of
algorithms. Since the center lacked a
professional, they had to hire external
technology personnel which would help
maintain the algorithm. The hire was an
expensive move. The mentioned are the
challenges and the opportunities that
the Cancer center managers
experienced in their quest to adopt AI for
the medical institution.

Management training program for AI in health
organizations
 There are steps in the training
program of adapting AI in the health
care system. The three steps are;
 Educate
 Enable
 Empowerment

Educate
 The first step of training is exposing the
staff to the algorithms and the AI. Education
on I begins at the campaign level where
every member is asked to get on board. The
managers have to show the local staff how
the AI will benefit the institution.
 Continued re training is conducted to affirm
the knowledge to the staff. Managers and
medical staff have become more valuable to
the company once they are trained.

Enable
 The enabling step involves giving the
staff access to different algorithms of AI.
It is through enabling the employees
that they discover ways of exploiting the
AI trend.
 Most medical staff will find AI
interesting. To find independence in
their jobs medical staff is likely to find
this stages a perfect opportunity for
adoption.

Empower
 Empowerment is the last stage in
training the medical staff in adoption
of AI. Empowerment is a stage where
the manager does not limit the level
to which the medical staff uses AI.
Through the staffs own initiative,
they can manipulate the AI algorithm
to do whatever they would like to
accomplish

Training results
 The medical staff engaged artificial
intelligence properly proving that they had
learnt a lot.
 There are a lot of feedback and
endorsements showing proof that the
program was accepted by many medical staff
 The medical staff have been able to come up
with a lot of artificial intelligence expansions
which is proof that the training went as
expected.

Conclusion
 From the analysis it is clear that
artificial intelligence as one of the
technological trends in recent times
has the ability of contributing a lot in
the health care industry.
 Health care managers in all the
sector of the industry should find a
way of incorporating the trend into
other sector of the public health

References
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