Consider this: 50 petabytes of data a year. That’s the amount of data a single hospital produces in one year. Now, expand that out to all the hospitals and other medical institutions around the world. This exponential growth of data is good on the one hand as it means we can learn from it, but on the other hand it has created a big problem.
According to the World Economic Forum, “in 2021, 60% of physicians reported at least one symptom of burnout and 70% of EHR users reported work stress from using health information technology.” These stats are scary, but data growth will continue, which means that people and organizations will look to AI more and more to help make sense of the data and how to use it to benefit patients everywhere.
With this in mind, it emphasizes the need for a balanced approach to how artificial intelligence works with the healthcare industry.
Why We Need to Assist AI
Left to its own devices, AI would run amok and hallucinate with outputs that, at first, might seem legitimate, but, on closer inspection, will be completely wrong. Now, put that into the healthcare context and you can quickly see the glaring issue.
That’s why there are several efforts in place to quickly put guardrails around AI to ensure that it stays within the boundaries necessary for privacy, quality healthcare, and continued innovation.
A couple of these efforts are a great start as they have captured the attention of the right people and organizations that can really make a difference.
The Coalition for Health AI (CHAI) has a goal to “develop ‘guidelines and guardrails’ to drive high-quality health care by promoting the adoption of credible, fair and transparent health AI systems.” The coalition is comprised of “1,300 organizations, including government and industry leaders, to build consensus-driven best practices and standards for using AI in healthcare.” This effort has received help from founding partners such as Amazon, CVS Health, Google, and Microsoft.
Speaking of Microsoft. It recently joined many other companies and institutions to form the Trustworthy & Responsible AI Network (TRAIN). According to Dr. David Rhew, global chief medical officer and vice president of healthcare, Microsoft, “When it comes to AI’s tremendous capabilities, there is no doubt the technology has the potential to transform healthcare. However, the processes for implementing the technology responsibly are just as vital.”
“By working together, TRAIN members aim to establish best practices for operationalizing responsible AI, helping improve patient outcomes and safety while fostering trust in healthcare AI.”
How AI is Assisting Us
Recently, Microsoft shared that they continue to see “AI adoption within healthcare grow, with 79% of healthcare organizations reporting that they’re currently using AI technology. AI also has a demonstrable business value, with healthcare organizations realizing a return on their AI investments within 14 months, along with an average return of $3.20 for every $1 they invest in AI.”
This type of return speaks volumes about the impact of AI within healthcare – and there is no sign of stopping. Case in point, a Microsoft company called Nuance Communications, announced that “Stanford Health Care – Stanford Medicine is deploying Nuance Dragon® Ambient eXperience
(DAX) Copilot across the enterprise to reduce heavy administrative workloads that lead to physician burnout and expand access to personalized, high-quality care by automating the creation of clinical documentation during patient exams.”
By directly targeting the burnout issues, this solution is already making a positive impact. According to a preliminary survey, “96% of physicians stated that it was easy to use, and 78% reported that it expedited clinical notetaking. About two-thirds reported that DAX Copilot saved time.”
Another example of how Copilot is making an impact in the healthcare industry is in the Crop Science, Pharmaceutical, and Consumer Health areas through efforts by Bayer.
“We are very open to trying new technologies, such as Microsoft Copilot, to stay at the forefront of innovation. Our employees have more power to support farmers, help cure diseases, and see consumers healthier,” says Christoph Sieger, Vice President, Head of Global Digital Workplace at Bayer.
Sarah Lewandowski, Global Technology & Innovation Lead at Bayer, shared that they have “more than 700 use cases for generative AI” and that “Copilot use cases are growing. In Microsoft 365, easily getting data from Excel files, creating a first draft in Word, or creating a PowerPoint presentation are some of the top examples.”
Literally building on top of the Copilot solution and its success, Bayer developed a Copilot plugin that they call Model Store. This solution is surfaced through Microsoft Teams and provides a way for data scientists and laboratory researchers to easily locate data faster. This data is part of the Bayer’s Crop Science division as they had developed a new way to manage research models for their work on identifying potential insecticides, fungicides, and herbicides to help farmers have their crops flourish.
“With Microsoft Copilot, researchers and data scientists can use a few key phrases to quickly locate studies and predictive models that can support them in their project challenges. Based on the experiences of Häse and Lewandowski, Copilot provides more than the relevant models; it identifies who is responsible for the research, making it easier to connect with the expert source on a specific topic. Ultimately, it helps the Crop Science division speed the laboratory processes to provide products to help farmers.”
Closing Thoughts
While many things that AI can do may seem like magic, when really, it’s reliant on three foundational things: data, guidance, and governance. Healthcare data volumes will continue to grow, industry rules and regulations still need to be adhered to, and security will need to be in place – and continually improved – to keep that foundation strong.
That’s why you and I – the people using Copilot and AI – MUST be involved to build on that foundation and keep a sustainable AI future for everyone. That may seem like a lofty goal, but it starts with simple things like:
- Reviewing the Copilot output in the Microsoft Business Applications you use each day to check for validity and then adding in your creativity and clarification.
- Asking questions or sharing your expertise with the user community to foster greater understanding of Copilot, the pros and cons, the pitfalls and successes, and more.
- Providing feedback to Microsoft, Partners, and ISVs that are extending Copilot to create awareness about responsible use and security during Community Summit.
- Attending the Copilot AI Summit Preconference to learn more about generative AI and Microsoft Copilot.
A couple of final thoughts… It’s very encouraging to see healthcare adopt AI and harness it for good. Further, seeing how Copilot is being extended for purpose-built use cases means that AI and healthcare will be partners for the foreseeable future.
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