For doctors, sleep apnea can be a particularly tricky condition to diagnose because, in the absence of pain or visible symptoms, even most people who suffer from the condition don’t know they have it.
In an effort to streamline the diagnostic process for sleep apnea, South Dakota-based Sanford Health recently unveiled an AI-driven tool that will, among other things, scan the organization’s EHRs for 67 potential indicators, including body mass index (BMI), age, gender, medical history, clinical symptoms and blood work. Combined with “sleepiness questionnaires,” the findings will result in a score indicating the likelihood patients are suffering reduced airflow as they sleep.
The tool works, said Max Weaver, the Sanford Health business intelligence analyst who developed the tool, “by using mathematical modeling to narrow the population down. It’s really from 1 million to perhaps 50,000. That kind of scale.”
Similarly, Kevin Faber, M.D., chair and medical director of sleep medicine at Sanford Health, explained, “It’s a tool to help identify risk. It’s not the diagnosis. It doesn’t replace the need for a sleep test. It doesn’t replace the need for the sleep consult for many patients. But it’s a tool that can help the primary care practitioner be ultra-efficient with his or her time, as they have precious few minutes with their patients and need to do the things that have the biggest impact.
This tool will allow them to then identify those patients at highest risk, so we can treat them for a condition that they didn’t know they had.”
As the article explains, each EHR already stores countless vital signs, laboratory results, medical history and other data. The AI filters through that information and ranks each person’s chance of having sleep apnea as low, medium or high.
“If you have only a couple of those risk factors, you would be at very low risk. If you had 50 out of those 67, you’d imagine ‘Holy smokes, they’re at a much higher risk.’ There’s a weighting of each of those risk factors. Each has a different impact,” Dr. Faber said.
The tool also displays the top five factors driving the score in each patient, which will change over time if the person, for example, stops smoking, loses weight or controls their diabetes.
“This AI algorithm automatically adjusts all of that,” Dr. Faber said. “For the primary care provider who wants to know, ‘Why is my patient at high risk?’ he or she can simply mouse over the icon and there’s your top five risk factors for that patient. Six months later those top five might be different. There will be an automatic re-analysis of every patient’s risk every month.”
Once a patient is identified as being at higher risk, the article adds, the provider may either refer them to the sleep clinic for evaluation and a traditional sleep study or they may order a home sleep test conducted through their primary clinic.
“All of this stuff is not to simply identify who’s at risk but to find whatever the right treatment for their apnea is, which is going to vary from one person to another,” Dr. Faber said.
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