Decision support tool in EHR helps detect acute kidney injury
The University of Pittsburgh Medical Center implemented a clinical decision support tool in their electronic health record system and were able to increase the detection of acute kidney injury, one of the most costly and deadly conditions affecting hospitalized patients.
Fourteen of UPMC’s hospitals used the CDS tool to monitor levels of blood creatinine—a standard measure of kidney function. Specifically, the computer program sent EHR alerts to physicians about changes in patients’ renal function to detect early stage acute kidney injury.
A new study conducted by UPMC and the University of Pittsburgh, which analyzed records from more than half a million patients admitted to UPMC’s hospitals, reports that the CDS tool resulted in a “small but sustained decrease in hospital mortality, dialysis use, and length of stay.”
According to the study published in the Journal of the American Society of Nephrology, patients with acute kidney injury experienced a reduction in hospital mortality of 0.8 percent, 0.3-day shorter lengths of stay and a decrease of 2.7 percent in dialysis rates.
“Acute kidney injury strikes one in eight hospitalized patients, and if unchecked, it can lead to serious complications, including the need for dialysis and even death,” said John Kellum, MD, senior author and director of the Center for Critical Care Nephrology at Pitt’s School of Medicine. “Our analysis shows that implementation of a clinical decision support system was associated with lower mortality, less need for dialysis and reduced length of hospital stay for patients diagnosed with acute kidney injury, among other benefits.”
While the changes were small, according to the authors the results are highly significant and if the computer program was applied to the national problem of acute kidney injury in hospitalized U.S. patients—about 12 percent or 2.2 million Americans annually—it would translate into more than 17,000 lives and $1.2 billion saved per year.
“Ultimately, we see this as confirmation that a fairly simple clinical decision support system can make a difference,” said co-author Richard Ambrosino, MD, medical director of clinical decision support and reporting at UPMC’s eRecord. “More sophisticated systems are possible and should have an even greater impact.”
As a result, Kellum plans to make improvements to the CDS tool by “working with pharmacists to adjust patient medications and machine-learning experts to better predict which patients will be at greatest risk for adverse events.” He adds that “incorporating protein biomarkers and even genomics into the system could one day revolutionize patient care, not just for acute kidney injury, but for other illnesses.”