GenAI is a Goal but Not the Destination in Healthcare

The term “artificial intelligence” now referred to as AI, was coined in 1950 when it was hypothesized that humans used information and reason to make decisions and solve problems. The thought of machines having that same ability didn’t seem too far out of the realm of possibility. What was once considered a breakthrough, is now a word engrained in our vernacular, and a goal we all raced to “accomplish” with an “adapt or get left behind” mentality. Generative artificial intelligence (GenAI), a new wave of intelligence that uses machine learning, is the next huge leap in progress and takes leadership to stay ahead, as this breakthrough technology iterates and learns at hyper-speed. 

For healthcare, despite possible skepticism, GenAI shows a significant amount of promise in the ability to help the industry become better, safer, and more efficient. It has even demonstrated its capability to be empathetic and help with doctor-patient communication. GenAI can improve workflows, which, in turn, reduces clinician burnout by automating administrative tasks and freeing up clinicians’ time for more patient-focused activities. A study found that GenAI could help reduce burnout by generating draft replies to patient inbox messaging, however, it failed to reduce the amount of time they spent on the task. This reiterates the importance of not losing sight of training methods and proper adoption, GenAI hype aside. Of note, the cost of GenAI’s implementation has also come into question, mapping back to the quality assessment of its capabilities when relating to patient care, beyond just the efficiency measures.

Here are four things for healthcare organizations and technology companies to keep in mind when embracing the inevitable next wave of intelligence:

1. Build trust. While GenAI and machine learning are revolutionizing healthcare, it’s important to remember that no innovation will happen without a human’s involvement in clinical decision-making. The trust and expertise of healthcare professionals are not just invaluable and irreplaceable, they are the very foundation on which GenAI integration in healthcare stands. Their involvement builds patient trust. Engaging clinicians early is not just imperative; it’s a testament to their importance in validating that solutions are clinically effective, safe, and seamlessly integrated into clinical workflows. 

2. Understand the cost investment for quality. As we work to ensure GenAI’s impact goes beyond efficiency, we’ll also want to assess the financial benefits of implementing the technology. In healthcare, there’s a high bar for excellence, as patients are at the forefront. Patients deserve answers and access to care as fast as possible, but the quality of the care received is paramount. “Good enough” doesn’t suffice in healthcare. Hospitals and health systems can’t discount quality when it comes to how care is delivered. The spotlight remains on where GenAI will have the biggest financial impact. Organizations are expected to spend $38.8 billion on GenAI in 2024, according to market research firm, International Data Corp. When making the investment to use GenAI at scale, there’s an inherent onboarding period that must be enacted. This could mean, financially, GenAI may not be helping the organization’s bottom line right away. Of note, medical errors, a leading cause of death in the United States, is not only devastating for the patient and their family, but errors of any kind can have substantial financial implications on the hospital or health system. GenAI can be a helpful vehicle for assisting clinicians in decision making, backed by data, to help prevent medical errors. But this is only true if the algorithm is fed accurate information and is created responsibly with a human in the loop. As the World Health Organization has warned, “Precipitous adoption of untested systems could lead to errors by healthcare workers, cause harm to patients, erode trust in AI and thereby undermine (or delay) the potential long-term benefits and uses of such technologies around the world.” 

3. Embrace collaboration. Disruptors are making blockbuster investments in healthcare and quickly learning that their traditional approach to solo innovation may not move the needle in solving the industry’s pain points. Even for the most established players looking to enter into healthcare, it’s quickly apparent that the promise of greater affordability, equity, and outcomes isn’t possible without partnership. Additionally, technical expertise aside, making an impact clinically, financially, or operationally requires a deep understanding of the user’s needs and preferences. Collaboration among partners that bring fresh thinking and an established understanding of the nuances of healthcare is not just welcomed, it’s essential.

4. Set the stage for what’s next. It’s estimated that 30% of the world’s data is generated by the healthcare industry, and growing. Therefore, if GenAI is the destination and machine learning is the vehicle that will take us there, then data is the electric charge that powers the journey. The next step in our progress is not just about GenAI or machine learning but about the curation of clinically meaningful and predictive data to power better care recommendations and outcomes. This data is key to unlocking the full potential of emerging technologies like GenAI that promise to augment clinical workflows and enhance patient care. However, if not dispersed efficiently throughout a hospital or health system, patient data isn’t being used to its potential. Furthermore, it’s not just about learning from within a hospital or health system, but being able to share learnings universally so that advancements in patient care is a collective outcome. 

Achieving superior outcomes and efficiency requires a unified foundation of evidence-based content and clinical perspectives that fuel all healthcare innovation and provide consistent care experiences amid the growing diversity of where patients receive care. We need a way to preserve the hope and promise of reduced burnout, diagnostic errors, and improved outcomes, while explaining how to break through the noise. We do this by embracing the advantages of the technology while remaining steadfast in ensuring all revelations that could impact patient care are responsibly and thoroughly vetted, while ideally enhancing the return on investment and improving patient outcomes. 

Keeping on top of the rapid pace of innovation is no easy task as it requires fostering a culture of continuous learning, collaboration, and the ability to stay nimble and adaptive. We can’t deny the vast impact that GenAI and machine learning have exemplified across industries, and the promise these advancements showcase for enhancing human ability and progress, when implemented correctly. GenAI will help healthcare reach its destination of efficiency and superior outcomes, but we can’t lose sight of the need for human touch, quality interactions and data to navigate us forward. Harnessing data and support tools to improve patients’ health can be extremely beneficial — when the cost doesn’t overshadow the quality. 

Photo: metamorworks, Getty Images

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