Exploring Uses for AI in Healthcare

While the full potential of artificial intelligence in the medical field is still on the horizon, the impact of AI in today’s healthcare is already evident, steering the industry toward more consumer-driven care and organizational efficiencies.

By Joyce Riha Linik

By Joyce Riha Linik February 13, 2024

Artificial intelligence (AI) promises to deliver unprecedented advancements in medicine in the years to come as researchers look at ways AI can be used to comb through vast databases to identify trends in varied populations, analyze molecular structures for possible drug candidates, and accelerate potential cures for diseases.  

But while these sophisticated applications are still on the horizon, AI is already making inroads in more basic functions, specifically in the areas of consumer-driven healthcare and organizational efficiencies.

“Most healthcare organizations would love to have all of the super sophisticated AI tools,” said Leah Gabbert, Marketing Director of Global Industry Solutions at Nutanix, who has worked in the healthcare industry for more than two decades. But, she explained, some of these  options, specifically the idea of leveraging AI for genomic-based precision care are still a bit “pie in the sky.”

“But the reality is that most healthcare organizations don’t have the specialized staff or resources to deliver that type of personalized medical care right now,” said Gabbert.


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Yet, AI is making its way into these organizations in fundamental ways.

“Right now,” said Gabbert, “we’re seeing a few consistent trends: first, consumer-driven care demands, and second, healthcare organizations recognizing the need to streamline their business to be more efficient but also to attract the very best clinicians and patient consumers.

Consumer-Driven Healthcare

From telehealth and remote monitoring to wearable devices and health apps, today’s consumers have access to more information than ever before, faster than ever before, which enables them to make more informed choices and play a larger role in their own healthcare.

During the Covid-19 pandemic, telehealth usage soared to 38 times pre-pandemic levels, according to McKinsey. Wearable devices and health apps, powered by AI algorithms, were also on the rise. In 2023, roughly 40 percent of U.S. adults reported using healthcare-related applications, and 35 percent wearable healthcare devices, according to a study conducted by the market research firm Morning Consult.


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This increased usage demonstrates growing consumer demand for accessible, personalized health data, as well as a desire on the part of consumers to play a role in managing their own individualized healthcare.

AI-driven chatbots and virtual assistants have also played a role.

“AI has changed how consumers investigate their own healthcare diagnoses,” said Gabbert. “All of a sudden, you can easily go to a website and say, ‘I have been diagnosed with Crohn’s disease. What is the smartest healthcare plan for me based on that diagnosis?’ And then you can go into a practitioner’s office with an idea of a suggested path toward your own healthcare.”

Gabbert noted that consumers can go online to see ratings and reviews for clinicians and facilities. They can check emergency room wait times. They can even price-shop basic procedures through some health insurance companies to see where they are getting the most value for their money.

Whereas, in the past, consumers had to rely on the expertise of local providers and facilities, they can now make more informed decisions regarding their healthcare. As active participants in monitoring their own health, they are better able to detect any potential issues and empowered to take proactive measures when necessary, thus taking a more preventative approach to healthcare.

“It’s wildly changed the idea that consumers can proactively manage their own healthcare,” said Gabbert, recognizing that consumers have a choice of providers, healthcare organizations have to meet their demands.

“Many healthcare organizations are focused first on the patient, and second on the balance sheet,” she said. “They are a business, and they understand that they have to attract patient consumers. They have to attract patients and be able to provide them a patient experience that will have them coming back, but will also have them speaking well about their brand in the community.”

Consumers have heard the buzz about AI and want to know how it can enhance their healthcare experience. In turn, healthcare organizations are working to deliver it.

Organizational Efficiencies

One of the ways medical facilities employ AI is to improve the administrative processes that keep the industry running smoothly. From simplifying medical coding and claims submissions to optimizing supply chains and enhancing lab procedures, AI is making its mark in healthcare management.

Historically, the claims submission process has been laborious and error-prone, given the large volume of incoming claims and the fact that each one had to be input and coded manually.


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Many healthcare organizations are now using generative AI to categorize claims, improving the accuracy and speed of the claim submission process. This results in a more streamlined process for both patients and the organization, plus faster reimbursements for providers.

Additionally, automating the claims process and review of medical records can save valuable time for healthcare professionals, enabling them to focus on more meaningful work.

“At the end of the day, leveraging AI for a critical workflow like claims submission is game-changing for getting reimbursements back into hospitals quickly, which helps with the bottom line,” said Gabbert. “It’s a quick path to being able to use AI and see an effect to the business right away.”

Healthcare organizations are also using AI to optimize lab procedures.

Laboratory personnel, including researchers, technicians, and managers, often face challenges maintaining up-to-date procedural templates and ensuring the consistent application of best practices, especially as scientific knowledge evolves. These challenges can lead to inefficiencies, errors, and inconsistency in experiments or analyses, often wasting time and resources in the process.


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Generative AI can streamline and enhance laboratory processes. By leveraging historical data and scientific principles, a Generative AI model could suggest novel experimental designs, more efficient processes, or alternate uses of reagents and equipment, stimulating innovation in laboratory procedures.

“I think we’ve all been in situations where we’ve gone to the doctor and we’re waiting for lab results, and sometimes those tests can be quick, sometimes they take a very long time,” said Gabbert. “Just being able to optimize lab procedures and have some sort of AI running faster so that you’re not just completely dependent on waiting for software to access only structured data, or humans to read labs. I think that’s going to help blaze trails.”

Additionally, healthcare organizations are turning to AI in the appeals process.

When a medical insurance claim is denied, hospital billing staff face a costly and lengthy process of reviewing patient records and medical policies to create an appeal letter. For U.S. hospitals, appeals-related administrative costs are measured in billions of dollars, largely due to the time required for staff to compile an appeal. While more than 60 percent of denied claims are recoverable, vague reasons for denial and limited hospital billing resources result in only 0.2 percent of in-network claims being appealed, with millions of dollars written off as uncollectable losses each year.


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A Generative AI retrieval model can sort through large volumes of medical policies and member plans to identify the necessary information for a claims appeal. Using extractive algorithms, the AI model can access unstructured medical notes, medications, lab results, and other electronic health records to pull pertinent information and then use an LLM to generate an appeal letter.

This process can greatly enhance the speed and efficiency of appeals and potentially recover more revenue.

“Being able to simplify and expedite that process will help not only the organization, but will also help expedite the right care for the patient,” said Gabbert.

In short, employing AI can help healthcare organizations simplify and streamline operations so that patients are getting the best care on the best timeline for the patient.

“There’s a very personal aspect to healthcare,” said Gabbert. 

“In a lot of industries, we talk about the fact that business is ‘business critical.’ But when we talk about healthcare, I’d argue that it’s not ‘business critical’ at all. It’s ‘life critical.’ We’re not talking about innocuous data points. Every data point on your list is a real person with a real medical need, and a decision can mean life or death to them.” 

Editor’s note: Explore how Nutanix software enables healthcare organizations to simplify IT operations and focus on delivering better patient outcomes and clinician productivity. And learn more about the Nutanix platform for AI, including Nutanix GPT-in-a-Box, a full-stack software-defined AI-ready platform designed to simplify and jump-start your initiatives from edge to core. 

Joyce Riha Linik is a contributing writer. Find her @JoyceRihaLinik.

© 2024 Nutanix, Inc. All rights reserved. For additional legal information, please go here.

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