Utilizing a pulmonary embolism evaluation algorithm to reduce unnecessary CT scans
Project Description: Patients being evaluated in the Adult Emergency Department (AED) at UF Health present with a wide variety of conditions, many of which may be life-threatening if not treated appropriately. One of the most difficult conditions to diagnose is pulmonary embolism as its signs and symptoms often overlap with other conditions. We will be instituting a clinically validated algorithm for the diagnostic evaluation of suspected Pulmonary Embolism in the AED using the Wells’ Criteria, Pulmonary Embolism Rule-Out Criteria (PERC), and Age-Adjusted D-Dimer to allow for appropriate risk stratification and avoid unnecessary testing with Computerized Tomography (CT) scans(1). Physicians from Internal Medicine, Emergency Medicine, and Hematology have collaborated to institute an evidence-based algorithm to direct the evaluation and work-up of patients with suspected pulmonary embolism. This multi-disciplinary team has implemented the algorithm and created a patient-centered decision aid tool. Recent best practice advice from the American College of Physicians have shown use of the PERC instrument in conjunction with D-dimer testing to be both safe and effective in the exclusion of suspected pulmonary embolism who are deemed to be low risk. The patient’s pretest probability of having pulmonary embolism should be determined by use of the Wells’ Score, a very well validated clinical instrument. Patients deemed low to moderate risk can be further stratified with PERC and age-adjusted D-dimer testing(see figure 1 below). This quality improvement project aims to reduce the rates of unnecessary computerized tomography scans in patients stratified to be low or moderate risk below age-adjusted D-dimer cutoffs for diagnosis of pulmonary embolism. This will ultimately reduce health care and unnecessary adverse effects associated with computed tomography imaging (e.g. radiation exposure and intravenous contrast associated adverse events).
QPI: Grant, Jester, (firstname.lastname@example.org)
Advisors: Anita, Rajasekhar, (email@example.com)
UF Health Big Aims: Increase Value None
MeSH Keywords: Algorithms, Diagnosis, Hematology, Internal Medicine, Pulmonary Embolism