In 2023, the healthcare industry was taken aback, faced with new challenges, and found inspiration in generative artificial intelligence (gen AI). We introduced and released a set of tools that can aid healthcare organizations in creating solutions using advanced AI technology. These tools include MedLM, a collection of models specifically tailored for healthcare applications, and Vertex AI Search for healthcare, which facilitates the discovery and analysis of relevant information.
In 2024, we can expect this technology to transition from experimental stages to practical applications in various fields. It will particularly focus on streamlining administrative tasks, aiding clinicians in accessing information, supporting healthcare call center agents, and ultimately enhancing organizational efficiency. In 2024, we can expect to witness ongoing experimentation with Gen AI for various use cases that demand thorough testing and development. One such use case involves the assimilation of information from diverse sources, such as medical images, textual clinical reports, and voice. This technology will ultimately revolutionize our understanding of health and healthcare.
I will discuss what I anticipate in each of these three areas: short-term optimization, long-term transformation, and profound learning. However, it is important to note that these areas are interconnected and not completely independent from one another. The initial actions individuals take to alleviate immediate paperwork challenges, for instance, will contribute to our comprehensive comprehension of general AI and optimal approaches in healthcare. That will have a significant impact on the major transformations we can expect in the next ten years. Put simply, significant changes don’t happen suddenly; they are developed gradually over time.
Optimizing administrative work with gen AI
Even for a system as dynamic as medicine and care delivery, the past few years have been unusually tumultuous. First, COVID-19 made stark the cost pressures, staffing shortages, fragmented technologies, and administrative complexities facing the industry on a global basis. Enter gen AI three years later, which can help relieve some of these pressures. For example, gen AI can enable easier document creation by digesting reports and long files for faster consumption, helping ease the administrative workload for short-staffed clinicians.
Generative AI can also ease the cognitive burden on caregivers by assisting with clinical documentation, easily finding relevant information, and by helping radiologists, pathologists, and lab workers go through large sets of results. Make no mistake, humans are more central to the process than ever, but with gen AI, they have a powerful new tool to do more satisfying work with less tedium.
According to the World Health Organization, there will be about 28 million nurses in the world in 2020. Save them just five minutes a day, and that’s 266 years better focused on patient care.
The point is not to free up that much time but to enhance the appeal of the profession. The WHO also says we’re short six million nurses. Incremental changes at scale create enormous change. To phrase it more simply: Less burnout, more satisfaction. Ultimately, restoring joy to medicine stands to benefit everyone.
Preparing for broad transformation built on gen AI
“Small differences making a big difference” is how the world of Gen AI is starting to bring about significant and impactful change. To provide two contrasting examples: HCA Healthcare, a prominent healthcare organization with a vast network of hospitals and ambulatory sites of care, is currently focused on developing Gen AI technology to enhance the process of patient handoffs among nurses. Meanwhile, Mayo Clinic, with its massive online audience, is implementing an AI-based enterprise search to enhance information sharing. This includes improving the understanding of symptoms as well as explaining drugs and treatments.
Whether it’s in the field of healthcare or any other industry, the advancements brought about by Gen AI may appear small at first glance. However, when we consider the long-term impact, it becomes clear that these advancements will lead to enhanced clinical documentation, more meaningful doctor-patient interactions, and ultimately, improved health outcomes for patients.
AI is making remarkable advancements in various fields, such as protein folding with AlphaFold. Additionally, it is poised to revolutionize our understanding of existing knowledge. There are fascinating opportunities for collecting and rearranging data in innovative ways. With the help of Gen AI’s powerful computing, a wealth of electronic health records, diagnostic reports, and PDFs can be analyzed to uncover new insights and patterns related to patient and hospital conditions. This, in turn, has the potential to improve the patient care experience and contribute to the overall enhancement of population health. MEDITECH is at the forefront of this field, simplifying the process of searching and summarizing electronic health records. Additionally, they have developed a feature that automatically generates an initial draft of the hospital course narrative upon discharge. What’s truly thrilling is the potential of Gen AI to revolutionize healthcare organizations by integrating data from various sources, including imaging scans, lab results, and patient interviews. By consolidating various pieces of information and data, Gen AI-powered solutions can effectively respond to medical inquiries with greater precision and safety. This is just the beginning of where this deeper comprehension is going.
Exploring the nuances of utilizing Gen AI in healthcare to enhance our knowledge
Healthcare is a field that offers unique rewards and presents its fair share of challenges. It combines the realms of science, humanity, and the business of providing care. It’s impressive to see how many skilled individuals in my line of work strive to constantly enhance the equilibrium between analytic rigor, empathy, and economic necessity. I take pride in being part of such a field.
In 2024 and beyond, there will be a significant advantage to be gained from gen AI as it fosters a deeper comprehension of all three domains. This is important for healthcare regulators who are seeking to comprehend and implement new technologies. It is of great importance to researchers and doctors who are seeking to gain a deeper understanding of patients and improve the effectiveness of treatments. Furthermore, this issue holds significant importance for healthcare companies and the countless patients seeking improved access to fair and efficient care.
In the near future, we’ll begin to develop a deeper comprehension of this. With a bit of good fortune and the tireless efforts of committed individuals, we can anticipate a profound and lasting evolution of knowledge.