The use of a clinical decision support tool significantly improved documented adherence to a national imaging quality measure, according to a study published in the March issue of Academic Radiology.
Although an evidence-based national imaging quality measure has been released regarding the use of CT for patients with suspected pulmonary embolism in the emergency department, many are not adhering to it.
“Computerized physician order entry systems with integrated clinical decision support have been suggested as a method for improving overall quality of care and and their use has been mandated by the Health Information Technology for Economic and Clinical Health Act and federal meaningful use regulations,” wrote lead author Ali S. Raja, MD, MBA, MPH, of Brigham and Women’s Hospital in Boston, and colleagues.
The researchers strove to determine the feasibility of using a national imaging quality measure-based clinical decision support tool to measure the adherence of CT pulmonary angiogram orders to an evidence-based national imaging quality measure. They also looked to identify if the increased burden of data capture affected the use and yield of CT pulmonary angiograms.
The study included 1,209 patients with suspected pulmonary embolism who were imaged during the 12-month control period. During the quarter 12 months after the quarter during which the intervention was implemented, 1,212 patients were imaged.
The documented baseline adherence to the national imaging measure was 56.9 percent. After the intervention, adherence increased to 75.6 percent. The CT pulmonary yield remained essentially unchanged, as it was 10.4 percent during the control period and 10.1 percent after the intervention.
“A national quality measure-targeted imaging clinical decision support enabled the granular clinical data collection needed to streamline the measurement and automate monitoring of emergency department provider adherence to evidence encapsulated in the CT pulmonary angiogram national quality measure, thus obviating the need for resource-intensive retrospective chart reviews,” wrote Raja and colleagues.