AI and Clinical Decision Support

Artificial intelligence is ushering a new era of healthcare tools. These range from ambient listening to streamlined practice management. But, the AI-supported that I believe will truly transform occupational therapy is:

Clinical Decision Support.

To be honest, it often feels like we have more clinical decision barriers than we have support. Our EMRs currently give us a set number of checkboxes, which massively pigeonhole our services, and often DO NOT reflect the kinds of best practice we teach here at OT Potential.

But, on the near horizon is dynamic point-of-service support that will help you choose the right assessments, set the right goals, and pursue the right treatment path for the patient in front of you.

Oh, and it will also be watching for red flags.

This is a lot to wrap our minds around. But, if we do it well, I think we will future proof our profession for changes to payment models and regulations, because it will so drastically increase our value.

In this course, we’ll review a new journal that outlines clinical decision support across 6 domains. Then, to walk us through what’s here now and what’s coming soon, I’m so thankful to welcome Brad Willingham, PhD, a clinical research scientist at Shepherd Center who has been focused on how AI is going to support clinical decision support.

1. You will recognize ways clinical decision support could help you make decisions at the point of care.

2. You will be able to identify the ways that AI will enable this real-time clinical decision support at the point of care.

• Intro

• Breakdown and analysis of journal article

  • Intro to AI and Clinical Decision Support

  • Intent of this article

  • Methods

  • The 6 domains of clinical decisions support

  • Conclusion and recommendations

• Discussion on practical implications for OTs

  1. Can you tell me about your current role & how you became interested in AI and rehab?

  2. How do you see AI improving clinical decision support?

  3. Coming from Shepherd Center, how have you historically thought about clinical decision support and how is AI changing your understanding?

  4. What were your impressions of this journal article?

  5. What types of applications of AI do you see emerging over the next few years in rehab?

  6. Can I tell you how I’ve been thinking about clinical decision support for OTs and get your reaction as to whether it is a good idea?

  7. What are your biggest hopes for AI in clinical decision support?

  8. What are your biggest concerns that we should be guarding against?

  9. This is such a big conversation. What concrete steps should we take today to prepare for a new future of healthcare?

Primary

• Advancing clinical decision support: The role of artificial intelligence across six domains

Additional

• Effectiveness of Artificial Intelligence (AI) in Clinical Decision Support Systems and Care Delivery

• Leveraging explainable artificial intelligence to optimize clinical decision support

It is the policy of OT Potential to disclose any financial and non-financial interest the provider or instructor may have in a product or service mentioned during an activity. This is to ensure that the audience is made aware of any bias of the speaker.

OT Potential pays guest speakers an honorarium for their participation, either directly or to an institution of the speaker's choosing at their request. We invite guests whose expertise often comes from practices, programs, or building products in their field. Where a speaker has a financial interest in the subject of a course, we disclose it below so you can weigh it for yourself.

OT Potential's interest in this topic: We have no financial stake in this topic.

Speaker interests: Brad Willingham has no financial interest in this topic to disclose.