During the pandemic, healthcare organizations are adopting digital technologies at an unprecedented rate. But significant misunderstanding remains about AI. In this article we address three commons myths about the technology’s origins and its role of AI in healthcare.
Providers have adopted new technologies for prevention and surveillance of COVID-19, as well as diagnostics and connected device monitoring. As a result, the amount of data produced has grown substantially. This data growth poises healthcare for a future where AI will play an increasing role.
So, let’s lay a foundation for that future. And better understanding is a great place to start.
Myth 1: AI is New
Alan Turing is widely regarded as the creator of modern computing. In 1950, shortly after creating the first physical computer, he conceptualized AI in a paper titled “Computing Machinery & Intelligence.” For the next few decades, AI research flourished, computer capacity advanced, and algorithms were developed.
So, why does it feel so new?
Those early scientists couldn’t access a fraction of the processing power that we do—even in their most advanced machines, such as the computer that landed Apollo 11 and its crew on the moon. Now, however, we have an abundance of opportunities for AI in the real world. That’s because we have the data to feed to sophisticated mathematical models and algorithms. We also have the computational power to process it in a reasonable amount of time.
Like a car, AI is not new. It’s just had major engine upgrades and an endless amount of fuel.
Myth 2: AI Will Replace Doctors
There are many emerging applications for AI in the diagnosis and screening of COVID-19. It’s an exciting time! But doctors now share the concern of other professions that they may be replaced by AI.
First thing’s first. At Calibrater, we believe that AI can make doctors better at their jobs. And the research seems to bear that out.
An Italian research team led by Davide Golinelli, MD, found that AI was being explored to solve all kinds of COVID-19 problems. AI-powered tools may be able to quickly detect novel coronavirus pneumonia in chest CT images, and blockchain and AI may be combined in a low-cost outbreak surveillance system. There may even be a chatbot on the horizon that takes in clinical and serological data (e.g., age, % monocytes) and spits out COVID-19 diagnoses. And the chatbot does this work with an astonishingly high rate of accuracy.
“The spread of COVID-19 appears to have finally provided an ineludibly sound reason to fully embrace the digital transformation,” according to Adoption of Digital Technologies in Health Care During the COVID-19 Pandemic: Systematic Review of Early Scientific Literature. The article was published this month in the Journal of Medical Internet Research.
The future is bright for AI as an augmentation of medical professionals. But AI is not—and never will be—a substitute for the care of a skilled and compassionate nurse, radiologist, or other provider.
Patient experience isn’t just a metric that healthcare business leaders care about. It’s a metric tied to health outcomes. The relationship that a patient has with their (human) provider is central to the delivery of high-quality care.
Myth 3: Artificial Intelligence Does Not Improve Patient Experience
Traditional thinking goes that patient experience is adversely affected by technology. Think of chatbots that lead to dead ends or annoying beeps when you’re trying to sleep in your hospital bed.
But with COVID-19, businesses have been forced to reduce waste and create operational efficiencies. They’ve adopted new technologies to manage their remote teams. As a result, comfort with video conferencing and telemedicine has grown substantially. We now know that patients report significant acceptance of the digital transformation of healthcare.
Likewise, AI can also be used to improve the patient experience. As an example, look at the Calibrater Health platform.
As we collect feedback from your patients, we create exactly the type of well-defined and abundant data that AI needs. We feed NPS scores and comments to algorithms that determine the sentiment of the patient. The best patient engagement platforms will be able to gain insight from this sentiment analysis—flagging problem areas with intelligent sentiment benchmarking.
In the fight for excellence in patient experience, humans and machines are on the same team. And Calibrater brings them closer together.
And so it goes with many of the myths surrounding AI. They’re often based on a misunderstanding of how it works. The truth is that AI can offer substantial improvements in productivity, safety, and patient experience. And as AI is finally getting the fuel it needs, the pandemic is accelerating this technology’s adoption.
Service Recovery Best Practices
We interviewed clinic managers, providers, and patient experience managers from our customer base to help identify the most crucial components of service recovery in the healthcare industry.