When AI experts are asked where they believe the technology will be most beneficial for humanity, one of the most common answers is healthcare. Proponents of the technology claim it will revolutionize everything from cancer diagnostics to drug discovery processes – helping the medical field take its next great step forward.
But how much of this is hype – and which use cases will truly prove robust?
This article answers these questions and explores the dynamics that will define the future of AI use in health.
The evolution of AI in healthcare has been extremely slow – until the last 18 months. A survey of physicians in 2019 found that just 5.9% were aware of AI healthcare solutions, whereas research from early 2024 found that three quarters of healthcare professionals are not only aware of AI – they anticipate widespread adoption of these solutions in the immediate future.
This shift is due to several factors, including widespread media coverage and growing industry acceptance of these solutions; the FDA has now cleared over 700 algorithms for use in healthcare.
When it comes to AI’s use in healthcare, studies repeatedly find contradictory beliefs amongst both providers and patients:
Ultimately, these tensions portray an industry still wrestling with the implications of increased AI adoption. The question now is: which use-cases will be so undeniably powerful patients and providers will be unable to resist?
The healthcare industry could reap a wide range of benefits from AI: McKinsey claims it will save the U.S. medical system $150 billion by 2026, while 83% of physicians expect the technology to lighten their administrative workload. But it is important to be clear about the limitations of AI – and focus on the kinds of tasks it can actually do better than humans.
The primary benefits of AI will boil down to three core factors:
AI can generate content, analyze data, and produce medical answers far faster than any human. This speed does not necessarily equate to accuracy; there will always need to be a “human in the loop” to correct errors and undertake quality assurance. But the sheer speed with which AI can undertake many repetitive tasks will enable healthcare providers to reduce delays in diagnosis, care, documentation, and various other important tasks.
There are a wide range of tasks within healthcare which humans can do – but would generally prefer not to. For example, primary care clinicians (PCPs) spend nearly twice as much time on electronic health record (EHR) tasks than on direct patient care. Using AI to automate these tasks will free providers to focus on patient care – where their specific skillset is most valuable.
AI solutions are able to identify tiny differences in images and find imperceptible patterns in data – enabling a level of analysis and accuracy humans cannot match. This will eliminate common human errors, such as inexact dosages and prescription mistakes. Equally, many specialists will use AI to augment their existing approaches and facilitate more precise treatment.
From identifying the best care path to submitting accurate HCC coding, a complete and accurate patient history is essential for any healthcare provider. But most organizations struggle with data gaps and silos, as information is either stored in multiple different systems or never properly documented. As a result, roughly 21% of patients say they have found inaccurate information in their medical records.
AI offers a powerful opportunity to bridge these data gaps – and this is one of the most popular growing use-cases for the technology. Using natural-language processing (NLP), AI solutions can ingest structured and instructed data from a wide range of sources to create a complete medical history.
Not only is patient data often incomplete – it is also difficult for healthcare personnel to use at the point of care. While physicians can access the EHR, they may not have the time or analytics to leverage that information in the ways they need to. This creates delays in diagnosis, trial matching, the creation of care plans, and various other important factors – all of which lead to poorer medical outcomes.
AI enables a range of medical personnel to access real-time analysis and extract important data at the point of care. This can accelerate and enhance a range of important tasks – from drawing conclusions from medical images to finding suitable clinical trials.
Healthcare providers are always weighed down by administrative tasks:
The net result? Lower patient engagement, less positive patient experiences, and unhappy medical staff.
AI solutions can automate a wide range of these tasks, from 24/7 scheduling tools to risk adjustment support software. This reduces the workload for administrators, frees providers to focus on patient care, and ensures every patient has an optimal experience.
Risk adjustment is vital for healthcare providers to receive accurate compensation from Medicare and other health plans. But the process of manually analyzing patient charts to identify and document all relevant HCC codes is not only time-consuming – it routinely leads to human error.
Most patients’ histories feature many different diagnoses, many of which the provider lack the expertise or experience in. This leads many diagnoses to either be overlooked or coded inaccurately, often leading to sub-optimal RAF scores – and missed insurance reimbursements.
AI solutions like HCC Assistant not only streamline this process by producing automated coding recommendations – they are able to accurately assess all patient data and ensure all relevant diagnoses are included. This saves time for providers, increases the accuracy of HCC coding, and ultimately increases the average provider’s RAF score by 35%.
Want to learn how HCC Assistant could improve your risk adjustment workflows?
