3 Takeaways to Guide Your AI Strategy

Encapsulating the recent Healthcare Information and Management Systems Society’s annual meeting can be like trying to devour an elephant. Where does one begin?

But for health care executives, key takeaways could be found amid the many discussions about artificial intelligence (AI) in all its forms and how the technology will continue to impact the field. Here’s what caught our attention.

1 | Take Control of AI

Health care’s need for actionable information is greater than ever, and AI is powering many ways to harness powerful data. AI tools are helping provider organizations conquer many repetitive tasks centered around listening, documenting and assisting clinicians and patients. Out of these early incremental advances, larger innovations have emerged, such as machines that can help physicians better diagnose disease.

How far and how fast should you go with AI? The key for hospitals and health systems will be to control how these advances are integrated into daily workflows to boost productivity, optimize clinicians’ time and expertise to improve outcomes while determining how the tools will be scaled.

Takeaway

This won’t be easy or without risk. To manage risk, leaders need to own whether, when and how AI technologies are used in the future, said Peter Lee, Microsoft’s corporate vice president of research and incubation. For now, leaders should focus on learning through AI applications, said Andrew Moore, CEO of Lovelace AI. Become comfortable now with the technology and its benefits and challenges.

2 | It May Be Time to Partner on Generative AI

Although still in their infancy in health care, large language models (LLM) received plenty of attention at HIMSS. These models are designed to augment things like administrative and clinical documentation and improve patient access to health information. But, as with many aspects of AI, there are concerns among providers about the accuracy and the potential for delivering misinformation if LLM tools aren’t well-managed.

As for where LLM tools like ChatGPT are heading, Microsoft announced that it is expanding its strategic partnership with Epic to try to harness the accuracy and efficiency of electronic health records (EHRs) and communications. Microsoft’s Azure OpenAI service will be integrated with Epic’s EHR platform. Among other things, this will allow Epic users to use natural language queries and interactive data analysis to Epic’s self-service reporting tool SlicerDicer.

Google, meanwhile, said it will soon begin working with a select group of Google Cloud customers to explore uses and share feedback on its Med-PaLM 2, a second generation of its LLM. A Claims Acceleration Suite is aimed at helping information flow from providers to payers with a special focus on pre-authorization. Google said it will focus on unlocking and presenting data, not making medical or claims decisions.

Takeaway

Exploring the potential for LLMs will be important as health care organizations assess just how far AI can propel them toward significantly higher levels of productivity, efficiency and safety. Again, though, identifying risks as well as rewards will be foundational to the process.

3 | Focus on AI Skill Development

Organizations like Kaiser Permanente and Intermountain started their AI journeys years ago and have progressed by addressing needed skill sets to achieve future aims. Much of Intermountain’s work centers on giving physicians the AI-powered data analytics needed to help patients live their healthiest lives possible and avoid high-cost care.

Kaiser Permanente has a similar focus and has delivered AI tools to improve daily operations. One tool alerts caregivers to patients with deteriorating conditions, predicting when a patient might need to go to the intensive care unit. The tool has helped reduce patient mortality by 16%, said Vivian Tan, vice president of strategic information management and global relationships.

Takeaway

These kinds of results don’t happen overnight. Any AI strategy should address needed talent and skill development. Kaiser hired its first user experience/user interface designer seven years ago, Tan shared in a panel discussion. To move health care forward, leaders must develop a new set of skills, said Tom Lawry, author and managing director of Second Century Technology, adding that AI is a top-emerging hard skill and design thinking is the top-emerging soft skill.


This article was reprinted with permission from AHA Center for Health Innovation Market Scan.

The original version of this page was published at:  https://my.shsmd.org/blogs/the-shsmd-team/2023/04/26/3-takeaways-to-guide-your-ai-strategy