Intelligent or Just Artificial? – The Emerging Quality Challenge of Dealing with Our Smart Machines

As quality professionals we are constantly striving to ensure that the “Umbrella of Protection” for our patients and organization doesn’t have any holes. We have methods to ensure the quality of our physicians, devices, processes, medications and facilities. Historically, most of these areas we could observe, inspect and evaluate for quality & safety, but as our machines get smarter what goes on ‘behind the scenes’ gets much more opaque (everything from Therac-25 to 737 Max). That is the whole area of embedded intelligence.

CMS requires that a quality program provide oversight of ‘Contracted Services’ which in some ways are the familiar black boxes of food service, cleaning, dialysis, compounding, organ management, remote rad reads and many other more sophisticated areas. The hospital owns oversight of critical work done by others. As equipment, software, methods, apps etc. get more and more sophisticated, embedded critical rules and knowledge become “black boxes” that have the potential to have a tremendous impact on our patients and healthcare organizations. While it may not be the responsibility of the Quality function to confirm the details of every embedded algorithm, there is a moral and likely regulatory obligation to be able to demonstrate quality oversight of the embedded intelligence. But how do we do that? What will that look like in five years?

In our professional roles, we need to begin to understand the increasing challenge and risk of embedded intelligence and what role we have in its oversight and how we can have a productive ‘seat at the table’. This is an emerging issue that will increasingly impact our organizations. This Learning Lab will provide a quick introduction to the challenge, some simple tools you can use now, and the awareness of how we can prepare our organization as well as our careers for these next challenges of the future.

Speaker: Ken Rohde, Sr Consultant

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Education​, Learning Lab

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