Today’s Role of AI in Healthcare

AI is a bit of a buzzword in some industries, the novelty of which either leads to widespread adoption or a quick turn to other, more relevant technologies.

This is not the case with healthcare. Outside of supply chain logistics and heavy industry, AI is finding major purchase in healthcare. Here, we will rundown why that is the case, and why AI in healthcare opens opportunities for the medical field to fundamentally transform how they cure diseases, create treatments, and supply care, especially during a global pandemic.

The Evolution of Healthcare with AI

While AI is making a significant imact in many industries, healthcare and medicine is one that is seeing huge progress with AI.

One aspect of healthcare that many of us might have experience with is logistics. With modern healthcare and insurance, the name of the game is paperwork and data. Forms, approvals, billing, triage… all of these are a significant part of the healthcare experience.

Some drawbacks of this include:

  1. Makes accessing care more difficult for patients. Understanding the ins and outs of insurance, forms, multiple billing departments, and more are major turn offs for patients who do not understand them. This frustrating ignorance of an opaque system only gets compounded during times of emergency–which is where patients often find themselves when interacting with hospitals or doctors.
  2. Makes executing healthcare solutions more difficult for on-the-ground practitioners, namely technicians and nurses. Nurses are the primary face of healthcare for many patients, which means that they also must manage all the paperwork and minutia that distracts them from their real jobs: providing care.
  3. Hospitals and medical networks need to have people on hand to handle patients and paperwork. As regulations and requirements grow, so too do the various levels of documentation. This means more people doing more paperwork and digging for more data when it is needed.

AI has had major success in addressing the above issues. Major pushes in AI for managing insurance claims, triage support, and initial testing and measurements have lessened the need for layers of bureaucracy while lightening administrative loads on nurses. That means that organizations save money and healthcare practitioners can focus on what they are paid to do: taking care of patients.

As AI has evolved, however, it has started to change conversations in medicine about predictive patient care. AI has been shown to accurately identify markers for health issues like cancer in patients scans, often more accurately than doctors.

AI has also played a role in clinical trials. Trained machine learning models can help organize data and provide insights into research results that may have slipped by doctors while ensuring that research follows protocols and compliance regulations at every step.

Care During the COVID-19 Era

In a perfect world, these advances are amazing and critical for the evolution of healthcare. With the emergence and persistence of COVID-19, however, the way that patients receive care has changed. With social distancing, highly contagious disease, and vulnerable populations, hospitals have been looking for new ways to supply care.

Cloud technology has been at the forefront of this battle. Collaborative tools, transparent databases, and unified interfaces have been critical not only in connecting patients and doctors, but also by keeping researchers linked so that they can continue critical research into vaccines.

AI is also starting to shape how healthcare works in a way that protects patients and caregivers. Remote care is a huge part of patient care during COVID-19, and AI is supporting at-home and telehealth support for patients that cannot, or should not, interact in public spaces. AI is also supporting doctors and nurses by processing test results to make suggestions based on that testing data combined with patient information and medical history.

The Bottom Line

Like any other industry, AI is only as effective in healthcare settings as the humans around it. The future of artificial intelligence for medicine is going to be in how it can collaborate with, and facilitate collaboration between, researchers, nurses, doctors and administrators. That means emphasizing partnerships between diverse stakeholders throughout the industry, naming challenges and obstacles through the plentiful amounts of data available and working together to clear them out to better serve patients.