Key Takeaways from Digital Health Counsel 2024 AI Summit
The Digital Health Counsel 2024 AI Summit recently took place in Seattle, WA. Attendees of the two-day event left with an undeniable realization of the profound impact that Generative AI (GAI) and data-powered innovation are having on healthcare.
Organized by Ogden Murphy Wallace and sponsored by Fenwick, a leading law firm for the tech and life sciences industries, the summit was a fantastic opportunity to connect and exchange ideas with fellow lawyers, in-house professionals, and AI industry leaders leading the way in this exciting space.
Here are a few key takeaways from the event, according to a Fenwick press release.
AI governance is taking center stage. AI governance is becoming an increasingly critical issue across industries, particularly in healthcare, as new legislation, rulemaking, conventions, case law, etc., continue to flesh out this fast-developing space. The EU’s AI Act has entered into force and is gradually entering effect alongside a host of state-specific legislation in the United States, including 17 AI bills recently signed by California Gov. Gavin Newsom covering a gamut of issues, including disclosure, transparency, and digital likenesses. But beyond these new laws, it’s important to keep track of various emerging AI governance frameworks, such as the National Institute of Standards and Technology’s AI Risk Management Framework, which is increasingly being featured in AI-specific legislation.
Don’t fear the regulator. While the FDA has not yet authorized any generative AI-based medical devices or issued formal rules specifically about GAI, the agency is actively assessing the technology and various regulatory strategies. However, digital health startups should not be intimidated; instead, they should employ best practices for engaging with the FDA and maintain open lines of communication to help minimize their risk. Given the unique aspects of generative AI, post-market performance monitoring will likely be an important regulatory tool.
Prioritize empathetic and ethical AI. Accuracy is not enough. AI—particularly in the healthcare context—must operate ethically and from a place of empathy. This starts with mitigating bias from the underlying data used to train the AI or machine-learning algorithm. Not only does that encourage more equitable and empathetic service for end users, but it can also reduce the risk of hallucinations that pose broader technical problems.
How BigRio Helps Bring LLM and Advanced AI Solutions to Healthcare
Like the key takeaways from the Seattle Summit, we understand the transformative impact that GAI is having on the healthcare industry. However, we also recognize that these kinds of moves toward greater use of GenAI-enabled technology must be done with care. In particular, the inherent issues of inaccuracy, bias, and hallucinations of commercially available GAI tools can be quite concerning in the healthcare arena.
In fact, a recent report produced by the AMA pointed out that many challenges remain before the medical industry embraces GAI on a major scale. Most of the concerns the AMA identified are problems when healthcare organizations and clinicians turn to “commercial off the shelf” GAI solutions such as those created by big tech companies like Google, Microsoft, or OpenAI.
But what if you could surmount privacy, bias, and other challenges by building a GAI-LLM model from the ground up for your healthcare organization’s unique targets and needs? You can, with BigRio’s Help!
BigRio has long been a facilitator and incubator in leveraging AI to improve healthcare delivery, originally in the field of diagnostics and research. We have recently been focusing our efforts on supporting startups and developing our own solutions that use LLMs and GAI to improve those areas of healthcare, as well as direct patient interactions, customer relationship management, EMR integration, and so much more.
We are proud to have recently launched our proprietary LLM-driven tool, Odyssey Accelerator. It is a first-of-its-kind solution that enables businesses of all sizes who want to use GAI to transform the way they search or query enterprise data, design workflows, derive enterprise analytics, report generation, dashboards, and more, to build a proof of concept before scaling it enterprise-wide.
Leading healthcare IT innovator Vivid Health partnered with BigRio to develop an LLM-driven end-to- end solution, that today can assess a patient’s status on any combination of more than 100 chronic conditions across sixteen specialties, generating personalized care plans at scale in under 30 seconds. That’s over 75 million possible care plan combinations in a fraction of the time it typically takes to pull together individualized plans. Its successful development and deployment stand as a testament to GAI’s potential to enhance the quality and efficiency of healthcare delivery.
Complimentary Gen AI Webinar: https://bigr.io/genai-webinar-december-2024/
You can read much more about how AI is redefining healthcare delivery and drug discovery in my book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI and machine learning are being used to improve healthcare delivery at every touchpoint.
