The Hardest Part of Clinical Training May Be Deciding When To Use It
Between courseware, tools and personnel time, the healthcare industry commits significant resources to clinical training, but data suggests we can significantly improve the return on this investment.
To illustrate this point, just look at the statistics regarding unanticipated adverse events in childbirth, a health crisis in this country finally coming into focus. Numerous studies, including those by the Centers for Disease Control (CDC), note that a staggering 50% or more of adverse events in childbirth are avoidable. Further digging shows that the vast majority of these unfortunate circumstances root back to “failure to diagnose and treat clinical warning signs.” These statistics have not significantly changed for years despite countless hours of sophisticated training by firms such as Relias with the product Gnosis. In 2014, perinatal leaders from HCA published a paper showing a significant reduction of adverse events in those patients that were treated in accordance with a specific checklist while receiving Oxytocin during labor. However, again, the outcomes data did not significantly drive change on a national level because this checklist is reliant on each individual nurse’s subjective interpretation of the patient’s state. In a very UN-scientific observation, an OB Department Chair at a large academic medical center once told me “when The Joint Commission asks me how we enforce our protocols, how can I in good conscience report that we adhere to standards when I can line up multiple nurses that look at the same fetal heart rate pattern differently.” A good but uncomfortable point.
So, when I read an article recently from Dr. Mark Simon of OB Hospitalist Group in which he suggests that “Every OB clinician across the country should be able to interpret a fetal heart rate tracing the same way, but the only way you get there is practice and routine education,” I have to disagree emphatically. It’s the right goal, but the wrong approach. Realizing Dr. Simon’s goal requires that we augment intermittent training with a persistent, consistent reference point. A control factor not reliant on human factors such as bias, exhaustion, lack of experience or emergencies on the floor. Use a software platform based on artificial intelligence (AI) that does just that. It recognizes troubling patterns the same way every time – every day, hour, second – and asks the clinician to simply “look at this please.” A system like this is the only way to approach uniform assessments. I am heartened that the American Association of Colleges of Nursing has publicly stated “We share an obligation for readying tomorrow’s workforce to understand how to leverage AI with strong nursing judgment.”
Let’s make sure we all maximize the valuable training in which we invest by aligning it with the proper supporting tools.
This article was originally published on PeriGen and is republished here with permission.
Carol Flagg caught up with Matt Sappern, CEO of PeriGen at HIMSS19 who shares his views on what he sees is broken in our healthcare system and discusses how technology, and specifically AI, can be used to improve clinical outcomes and financial ROI for organizations. Take a listen.