Five ways generative AI is improving healthcare today and defining its future

“We are moving from the sterile clinical occasional care of an analog past to a promising real-world high-fidelity future,” Nirav R. Shah, Stanford University School of Medicine Senior Scholar at the Clinical Excellence Research Center, predicted to the VB Transform audience. “I think that I can’t give you the map of where we’re going. But I can give you a compass. I can point you toward TrueNorth,” Shah said.

Shah continued, “Generative AI is transforming the care we provide, enabling personalized treatment plans, real-time patient monitoring and advanced diagnostics. These advancements not only improve current healthcare delivery but also pave the way for future innovations.”​

The future of generative AI in healthcare

“Healthcare is not productive. The more technology we get, the less productive we become. As a doctor, it used to take me 45 minutes to admit a patient in the paper-based world, and now, thanks to electronic health records, it takes me an hour and 45 minutes because I’m a glorified data entry clerk. Technology hasn’t worked for us,” Shah explained.

Healthcare systems historically have lacked user-centered design, prioritizing billing and administrative functions first. Shah contends that designing healthcare systems with those criteria has led to physicians and medical care providers spending an increasing amount of their time doing data entry and navigating complex interfaces.

Shah says that generative AI can change the direction healthcare is going with technology and enable greater patient care while reducing the drudgery and delays in administrative tasks the industry is known for.

Emphasizing the many patient and medical provider benefits of streamlining and personalizing healthcare with generative AI, Shah says the industry is in the beginning stages of realizing gen AI’s full potential. Prioritizing the performance gains potential from using AI to streamline the often manual and time-consuming administrative processes, healthcare shows strong upside potential. Gen AI is already making contributions to improving patient care, greater accuracy in patient and care diagnostics and enabling real-time insights to improve clinical decision-making and research.

“Generative AI is transforming the care we provide, enabling personalized treatment plans, real-time patient monitoring, and advanced diagnostics. These advancements not only improve current healthcare delivery but also pave the way for future innovations,” Shah observed.

Shah explained that generative AI will enable a new value-based redistribution of intensity. Instead of matching risk to care intensity, gen AI will enable a new value-based distribution of care that will deliver more effective health outcomes. The following slide from Shah’s presentation illustrates the point.

How gen AI is driving healthcare to a high-fidelity future

“AI is fundamentally reshaping healthcare by enabling unprecedented levels of precision and personalization in patient care,” Shah told the audience.

“With AI, we are moving towards a future where diagnostics are faster, more accurate, and tailored to individual patient needs. This transformation is not just about efficiency; it’s about enhancing the quality of care and outcomes for patients. AI’s ability to analyze vast amounts of data allows for early detection and intervention, significantly improving patient prognoses and overall health,” he said.

The following are five ways gen AI is improving healthcare today and defining its future:

Improving diagnostic accuracy. Training large language models (LLMs) to better diagnose diseases and provide greater accuracy in detecting them by combining multisensory input is defining the future of healthcare today. Shah called for more effective integration of real-time data to improve diagnostic accuracy and more effective tracking of early disease detection. Future tools in this area need to integrate real-time data for instant diagnostics and make the most of available genetic data and wearables.

Enhancing patient care and management. Shah made a compelling case for using gen AI to improve in-home patient care with AI-driven telehealth and virtual platforms to improve healthcare access. He also underscored how the future of healthcare will be defined by personalized treatment plans using patient data, improving patient care. Gen AI can also aid in chronic disease management with real-time monitoring and interventions. Future telemedicine will expand with continuous remote care. “More care is shifting into the home, not being episodic four times a year with your doctor,” Shah said.

Streamlining administrative processes. Shah predicts one of the most significant gains gen AI can make in healthcare will be in streamlining administrative processes. Automating scheduling, billing, and documentation and reducing provider workloads are just a start. Shah says there are exceptional gains to be made in improving administrative processes and automating them with gen AI to improve efficiency. He predicts that chatbots and virtual assistants will eventually handle patient inquiries, enhancing experience and efficiency. The goal needs to be improving the level of patient care by combining the latest technologies with real-time telemetry that can identify potential conditions and be pre-emptive in treatments. Shah is optimistic about the future, noting that gen AI in Healthcare AI will fully automate workflows, enhance predictive analytics for resource management and improve interoperability across systems. He believes that the next wave of AI advancements will address these longstanding issues, providing more seamless and efficient healthcare delivery.

Supporting clinical decision-making. The potential for gen AI to support clinical decision-making is just getting started, according to Shah. There are going to be more advances made in AI-driven support systems that provide evidence-based recommendations, leading to more informed decisions faster. Shah also believes that gen AI will help enhance treatment outcomes with tailored suggestions and monitor vitals for timely alerts. Implicit across his presentation is the role of advanced AI in offering real-time support during surgeries and critical care, predicting patient deterioration and improving clinical guidelines.

Revolutionizing research and development. Core to the high-fidelity future Shah referenced in his keynote is the need to get the full value of gen AI applied to improving medical research and development. Accelerating drug discoveries, reducing time and costs for clinical trials and identifying new uses for existing drugs is a start. Future AI-enhanced personalized medicine will offer genetic-based treatments, improving efficacy. It’s feasible that gen AI will drive genomic studies, discovering new biomarkers and advancing disease understanding.

On the brink of a high-fidelity healthcare future

“Generative AI is transforming the care we provide, enabling personalized treatment plans, real-time patient monitoring, and advanced diagnostics,” Shah explained. The future of healthcare will be defined by the real-time nature of data integration and sharing, combined with greater precision and personalization, ultimately enhancing patient outcomes and overall health.