Artificial intelligence-enabled test may substantially reduce costs related to diabetic kidney disease
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For patients with diabetic kidney disease, using an artificial intelligence-enabled diagnostic test to predict rapid kidney function decline and kidney failure could result in substantial savings to the U.S. health care system, a speaker told the audience at the virtual National Kidney Foundation Spring Clinical Meetings.
According to Thomas Goss, PharmD, of Boston Healthcare Associates, the current method for risk stratification in diabetic kidney disease fails to identify about half of the patients who ultimately have rapid kidney function decline. Furthermore, up to two-thirds of these patients initiate dialysis acutely due to a crash which, he argued, is a very costly way to initiate dialysis.
“We know that many patients who are at high risk [for rapid kidney function decline and failure] often don’t get referred from primary care physicians to nephrologists early in the stages of the disease when the most opportunity for intervention is available,” he said. “We feel there’s an important need for a predictive tool that will help us to identify patients at high risk and improve our intervention strategy.”
Goss added that $42 billion is currently spent by Medicare on this population annually (patients with type 2 diabetic kidney disease stages 1 to 3b).
Following a hypothetical cohort of 10,000 patients for 5 years, researchers developed a budget impact model to compare potential cost savings with the diagnostic tool (which put patients into risk categories) vs. standard of care. Considered costs included test cost ($950), prescription medications, specialist and associated office visits, hospitalizations and other complications.
In the 5-year period, implementation of the diagnostic test led to a projected savings of $115 million (ranging from $83 million to $130 million). According to Goss, the savings stem from slowed progression, delayed/avoided dialysis and transplants and fewer crashes.
“With early and accurate risk stratification that identifies patients with diabetic kidney disease who are likely to experience rapid kidney function decline or kidney failure, the use of the AI-enabled diagnostic test has the ability to generate significant cost savings to payers through improved care management at earlier stages of the disease,” Goss contended.
In addition, he said, the tool would support primary care physicians and endocrinologists in identifying patients who can continue to be monitored in those practices (low risk) and where more timely referrals to nephrologists may be appropriate.
“Improving the health care system’s ability to provide care that conforms to [Kidney Disease: Improving Global Outcomes] KDIGO guidelines at earlier stages should help to reduce progression from diabetic kidney disease to ESRD and have a substantial clinical and economic impact,” Goss concluded.
The test, known as KidneyIntelX, has already received breakthrough device designation from the FDA. – by Melissa J. Webb
Reference:
Datar M, et al. Abstract #479. Presented at: National Kidney Foundation Spring Clinical Meetings; March 26-29, 2020 (virtual meeting).
Disclosure: The study was funded by a research grant from RenalytixAI plc.