To better understand the potential impact of generative AI in healthcare, we posed the following question to a number of health IT experts:
How do you think generative AI might reshape healthcare in the next year or two, and what transformative effects could this have for your role and/or your organization?
Their responses on the future of healthcare technology emphasize the broad impact of generative AI, including improvements in areas like patient care and administration, while also acknowledging the challenges of AI integration when it comes to data privacy, ethical usage, and balancing technology with human judgment.
To read their predictions in full, read our insight brief, The future of healthcare with generative AI: Hopes and hesitations. (Too much to take on right now? No worries. Keep scrolling for a couple of excerpts.)
Accelerating solutions with LLMs
There are two major problems in healthcare. First, almost 80% of healthcare data is unstructured, making it difficult to action on. Second, there’s a lack of connectivity across numerous data assets in healthcare, hindering their full usability. I am excited for 2024 as I believe that the rise of large language models (LLMs) and generative AI capabilities have given us a new toolkit to tackle those challenges. With them, we can solve the unstructured data problem in a meaningful and robust way while also accelerating the solving of the second problem. We have been resolving the second dilemma by leveraging approaches such as rules-based schema, developing better ontologies, and building knowledge graphs (a data source that has sources linked and connected). I believe generative AI can help further accelerate this process. Hassan Bhatti | Product and Partnerships of Data Marketplace, SnowflakeAmplifying intuitive technology
As a chief AI architect in healthcare data processing, I see generative AI revolutionizing application development by simplifying the interaction between healthcare professionals and data. It’s about creating applications that are more intuitive, allowing for complex data analyses without the need for deep technical expertise. This democratization of data means that we can develop applications that fit naturally into a clinician’s workflow, enabling them to make informed decisions quickly and efficiently.
From an application development standpoint, the focus will be on user-centric design — building systems that are not only powerful in their analytical capabilities but also seamless and straightforward to use. The aim is to reduce the friction between the vast data that healthcare organizations handle and the actionable insights they need.
In the next couple of years, I anticipate that my team will be at the forefront of integrating generative AI into our organization’s solutions, focusing on enhancing user experience and clinical decision-making. Generative AI will lead to smarter applications that amplify the capabilities of healthcare providers, driving our organization towards a future where technology is a natural extension of the care team’s expertise.
Jingqi Wang, PhD | Senior Vice President of Data Science and Chief AI Architect, IMO Health
