We can all agree that the world of healthcare has drastically changed over the past years. We can also agree that it has changed for the better. It’s hard to imagine that decades ago, before you undergo certain medical procedures requiring anesthetics, you’ll have to choose whether they use anesthetics for your entire body or none at all. This is because the invention of localised anesthesia hasn’t been done yet. Important technological devices such as X-rays and CT scans revolutionised the way illnesses are identified. Diagnosis are more accurate and efficient—and these devices aren’t available in our hospitals decades ago. We can also observe that hospitals now have means of communicating with each other more efficiently. This advancement helps save lives everyday. In healthcare research area, we continue to discover more and more cures, vaccines, and preventive measures towards sicknesses that decades ago might seem incurable.
Today, we live in an interesting time with the integration of Artificial Intelligence or AI in the healthcare industry.
Problems in Healthcare that AI is attempting to solve
We enter a phase in healthcare where AI is gaining popularity, as man attempt to solve the remaining healthcare problems. The three main dilemma we’re having are what experts call the “iron triangle”—access, affordability, and effectiveness. The goal is to improve or solve these problems without affecting the other, as what our current technology does.
Access
When we talk about access to healthcare, it usually means that it’s a question on how easy (or hard) it is to get medical advise within our locale. A simple example on how AI helps improve the lack of access to healthcare is developing virtual nurses. Just like Google Assistant, these nurses can monitor the patient’s vitals. They can also remind the patients of their medication. Another example is AI is now developing the technology that can diagnose sicknesses accurately and efficiently. Large scale production of these assistants lessens the need of having many doctors and nurses in a locale. This helps solve the lack of access in healthcare.
Another aspect of AI in healthcare that provides accessibility is by the use of smart phones and other remote devices to monitor health. We have devices monitoring our oxygen level, or if we’ve been been idly sitting for a long time. These devices also record the daily routine of the person and gets more intelligent over time. It also leads to more sound recommendations on how to take precautionary measures about one’s health. The best part is that they don’t need frequent visits to the doctor to achieve this.
Affordability
Research says that there are “wastages” happening in healthcare every year due to inefficiencies such as misdiagnosis or over treatment. The amount spent on those inefficiencies could have been properly allocated to different medical subsidies and could have made healthcare more affordable. One of AI’s goal is to help minimise such wastages by introducing applications that can perform uncomplicated tasks such as analysis of scans and tests with utmost accuracy. These applications reduce physician error and enables early diagnosis and interventions before conditions become critical.
Another example is the invention of AI enabled watches which promotes self-awareness about health. We’ve seen in the past years that more people are using these watches to monitor their sleep patterns, heart rates, and even or calories burned. Usage of these devices can potentially prevent sickness, and as we always say, prevention is always better (and cheaper) than cure.
Healthcare will also benefit greatly from AI advancements specially in drug development. AI can simulate and analyse millions of data points such as potential medicines for certain sicknesses. These tests can be done by AI without having physical tests and are highly accurate—saving money and saving lives as well.
Effectiveness
AI generally works by feeding on information relating to its subject. Afterwards, these data will be the basis of the decision and action of these AI devices. Many of these AI applications have shown promising results. They’ve exhibited that AI powered machines can perform tasks with efficiency and accuracy. There are a number of case studies already introduced that relates to healthcare. An example is an AI technique used to find out which genes are causing antibiotic resistance. Another example is an AI technology being used in cardiology that monitors heart rhythms that can detect a heart attack. These case studies have already proved their effectiveness. With the help of doctors and researchers, the industry is creating applications and machines that are AI enabled whose purpose is to provide excellent healthcare.
AI Problems In Healthcare
A number of problems might arise in the dawn of AI in healthcare. We need to face these challenges head on, since the future of AI is so promising that we can’t afford to hold ourselves back. Below are some of these challenges and how we can solve them.
Ethical Implications
We need to consider the several ethical implications of the use of AI. Since AI doesn’t have the ethical consciousness that humans have, making sure that AI has human oversight is essential to prevent ethical problems such as discrimination or violation of patient rights. Healthcare organisations need to reinforce AI Ethics as early as now. This will determine the advancement of the very technology they are aiming to develop.
Public Acceptance
It is understandable that many people will not initially accept AI as a healthcare solution. The key is to effectively articulate the processes behind the AI related services. Over time, just like how we trust x-rays and CT scans now, AI will be accepted by majority of the population.
Threat to Human Jobs
We’ve heard this before- AI is taking over human’s jobs and we’ll be out of jobs real soon. This is partly true, as AI’s main goal is to remove the repetitive jobs such as administrative tasks in healthcare. However, we believe that taking humans out of the equation specially in healthcare has low probability. Even if AI can do all the tasks that doctors and nurses can do, there are still tasks that will need “human connection” that AI cannot replicate. We also stated above that AI needs human oversight to prevent it from doing unethical decisions and actions. We believe that by removing the repetitive tasks from humans, AI allows doctors and nurses to focus on more important duties rather than doing administrative works and repetitive tasks.
The examples stated above are minute compared to the number of emerging technologies that are currently in the pipeline for AI in healthcare. It is undeniably shaping the numerous aspects of the industry. We see many private and public sectors in healthcare investing on AI to improve healthcare services as well as to minimise costs. This is an indication that AI in healthcare will be the norm in global health practice in the near future. The possibilities of AI applications in healthcare are boundless.
