Study of Automated Care Pathway for Patients With Chronic Obstructive Pulmonary Disease (COPD)

This is a single-center, single-blinded, 2x2 factorial randomized controlled trial to test both automated order set inclusion and evidence-based order set design with end user testing on order set use and clinical outcomes for adult patients admitted to the hospital with acute exacerbations of Chronic Obstructive Pulmonary Disease (COPD). First, the investigators will develop a predictive model to identify patients admitted to the hospital with COPD exacerbations based on retrospective data, but limited to data that is available in real-time at admission. Second, 1,000 admissions to UCSF Medical Center of adults predicted to have COPD by the predictive algorithm will be prospectively block randomized by encounter to automatic inclusion of a COPD order set in the admission orders or usual care. Providers caring for patients in both arms of the trial can independently search for and use a COPD order set. Any provider using a COPD order set in either arm will also be randomized to see two versions of the order set. The first is a static list of orders, and the second is dynamic, meaning that orders will display only when appropriate. For example, a patient who just had a chest x-ray does not need a routine repeat test. The dynamic order set will show the provider that the x-ray was completed at a specific time and will not display a prompt for a repeat test. Providers can, of course, still order anything they deem clinically appropriate, and may choose to order a repeat x-ray for a patient with a change in clinical status. The components of the order set are based on international guidelines from the Global Initiative for Chronic Lung Disease (GOLD initiative, a collaboration between the National Heart, Lung, and Blood Institute and the World Health Organization) and a multi-stakeholder working group at UCSF including two hospitalists, two pulmonologists, two transitional care nurse specialists, one advanced practice nurse, one pharmacist, one respiratory therapist, one physical therapist, and one nurse.