Close

See How Your Peers Are Moving Forward in the Cloud

New research from CDW can help you build on your success and take the next step.

Oct 03 2024
Artificial Intelligence

AI in Healthcare: How It’s Used and Future Use Cases

Different forms of artificial intelligence are having a substantial impact on the healthcare industry, and the use of AI is expected to grow substantially in the near future.

The healthcare industry is using artificial intelligence to elevate patient care and alleviate administrative burdens on a wide scale, with 79% of healthcare organizations reporting that they have adopted AI technology in some capacity, according to a study commissioned by Microsoft. 

It’s important to remember that the idea of a sentient and self-aware AI capable of offering healthcare on its own is still science fiction. While current AI applications in healthcare can help improve clinical efficiency, advance research efforts and aid in precision surgery, they are tools designed to enhance human work.

“With AI, we don’t replace intelligence,” says Jason Warrelmann, vice president of healthcare industry at UiPath. “We replace the extra hours spent doing tasks on the computer.”

PREPARE: Expert guidance helps healthcare organizations achieve meaningful transformation with AI.

What Is AI in Healthcare?

AI in healthcare is categorized in two ways; the first is based on a system type’s functionality. But all AI is not created equal.

The predominant system type in use today utilizes limited memory. These machines build on available data to learn and make predictions. The most well-known example of a limited memory system is ChatGPT. 

The second categorization is by level of intelligence. All current AI tools have artificial narrow intelligence, which means they are designed to perform only specific functions. 

More advanced system types — with artificial general intelligence or superintelligence that enables the machine to understand human emotions or have desires of its own — are strictly theoretical.

Click the banner below to effectively use technology that helps providers deliver better care at a lower cost.

 

What Is the Difference Between Augmented Intelligence and Artificial Intelligence in Healthcare?

The term AI is used generically, but it actually refers to two forms of intelligence. 

Artificial Intelligence

An artificial intelligence is designed to perform tasks autonomously. One example is the DAX Copilot from Microsoft, which listens and takes notes during healthcare appointments. It analyzes the data and generates a clinical summary that can be added to the electronic health record.

Augmented Intelligence

Augmented intelligence refers to devices that are created to help people work more effectively. Augmented intelligence tools in radiology, for example, can be used to analyze images and detect anomalies.

“I think the biggest impact in healthcare is from augmented intelligence,” says Chris Darland, CEO of Peerbridge Health. “You’re making better tools for the doctor to help them do their job.”

How Is AI Being Used in Healthcare?

Current AI applications in healthcare span multiple areas:

AI in Medical Diagnosis

AI can analyze medical data sets more thoroughly than a human can and won’t get tired in the process. As described above, tools powered by augmented intelligence are currently used to assist radiologists. Systems like the Precision Imaging Network from Nuance Communications examine images such as MRI scans and X-rays to help radiologists make the most accurate diagnoses possible and detect diseases sooner.

Wearable devices are also helping to improve patient outcomes by gathering critical data that can inform care decisions. For example, Peerbridge Health developed an AI-powered, wireless electrocardiogram patch that monitors cardiac activity remotely. “It gives cardiologists a full view of the heart,” Darland explains, “and the data can be used to create a treatment plan.”

AI in Drug Discovery

Clinical drug development projects take several years and have a 90% failure rate, but AI has the potential to enhance this type of work. Systems such as AlphaFold 3 from Google are designed to help researchers better understand how different molecules will interact and help them predict whether a particular drug structure will be effective against diseases.

Armed with this data, scientists can “find the winners faster, which means getting to clinical trials sooner and helping more patients,” Darland says.

Advancements are happening in real time. A team at Stanford Medicine, for example, says it used a generative AI model called SyntheMol to develop drugs that target antibiotic-resistant bacteria.

READ MORE: What does the growth of generative AI mean for drug discovery and clinical trials?

AI in Patient Experience

Healthcare chatbots are increasingly used to assist patients with routine tasks such as scheduling appointments and requesting prescription refills. Tools such as IBM Watson Text to Speech service enable healthcare organizations to communicate with patients in multiple languages.

Electronic patient portals are being used to enhance patients’ experiences at in-person appointments, Warrelmann explains. “We have a customer whose GPS-enabled health app, with the help of AI, knows when a patient arrives and automatically checks him or her in,” he says. “It verifies insurance and pulls up the patient’s chart. It makes the intake and triage process more efficient.”

 Jason Warrelmann
If you democratize AI and make the systems more intelligent, I think we’ll see patient and provider experiences improve.”

Jason Warrelmann Vice President of Healthcare Industry, UiPath

AI in Healthcare Data Management

AI applications are making it easier for healthcare organizations to analyze large data sets and share them with different systems or departments.

“With data management, it’s about interoperability and data transformation. We see this often with EHR migrations,” Warrelmann says. For example, “you may have decades worth of documents. An AI can download, translate and audit the data in real time.” 

AI in Robotic Surgery

AI-powered devices are helping surgeons perform minimally invasive procedures with smaller incisions and greater precision. Robotics help reduce the risk of errors and complications by giving surgeons better visibility and greater range of motion. The da Vinci Surgical System is one of the most common AI-powered devices in use worldwide

“It’s not like a robot welding a door onto a care,” Darland stresses. “This is augmented intelligence. A doctor is still operating the robot.”

The Future of AI in Healthcare

Data suggests the use of AI in healthcare will expand substantially over the next decade. Researchers project it will grow from a global marketplace value of almost $27 billion in 2024 to more than $613 billion by 2034.

Warrelmann says he anticipates AI will help bolster medical education and specialty training. “I think we’ll see medical students being certified sooner and having the tools to be more productive in healthcare.”

Darland predicts AI applications could be used to strengthen patient data security. “To train these AI models and detect patterns, they need a lot of cloud-based data, and there are questions about how we safely manage it all. I’m convinced AI will fix that.”

Both Darland and Warrelmann emphasize that AI-powered systems that are designed to lighten clinicians’ administrative load will have the biggest impact on healthcare in the near future. 

Spending less time on documentation and submitting billing codes could help relieve burnout, Darland explains. “I think keeping physicians engaged and excited about their job and reducing the burden of menial work for nurses will have a big impact.”

“If you democratize AI and make the systems more intelligent,” Warrelmann adds, “I think we’ll see patient and provider experiences improve.”

gorodenkoff/Getty Images