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

NCT ID: NCT03028805

Last Updated: 2019-06-18

Basic Information

• Recruitment Status: TERMINATED
• Clinical Phase: NA
• Total Enrollment: 310 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2018-03-26
• Study Completion Date: 2019-01-23

Brief Summary

This is a fully automated randomized trial with two randomization branch-points. The first is inclusion of disease-specific orders in the admission orders based on a predictive model using real-time data. The second is the use of dynamic orders that are end-user tested rather than static orders designed by a committee. The primary hypothesis is that automatic inclusion of disease specific orders with admission orders will improve adherence to guidelines for patients with COPD. The secondary hypothesis is that clinical and operational outcomes will improve, thereby improving value.

Detailed Description

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.

Conditions

Pulmonary Disease, Chronic Obstructive; Pulmonary Diseases, Obstructive

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: FACTORIAL
• Primary Study Purpose: TREATMENT
• Blinding Strategy: SINGLE

Study Groups

Usual care and order set A

Usual care. Providers may still search for a COPD order set, and in this arm will see version A, the static list of orders, which is the current state.

Group Type: NO_INTERVENTION

No interventions assigned to this group

Usual care and order set B

Usual care in the sense that COPD orders are not automatically included in admission orders despite likelihood of a COPD admission based on the predictive model. However, providers may still search for a COPD order set, and in this arm will see version B, the dynamic list of orders that has been end user tested prior to launch.

Group Type: ACTIVE_COMPARATOR

Dynamic, end-user order set design

Intervention Type: OTHER

Use of a dynamic order set that has been end-user tested prior to launch rather than designed centrally by a committee to test use of order set components.

Automatic inclusion and order set A

COPD order set is automatically included in admission orders as a static list.

Group Type: ACTIVE_COMPARATOR

Automatic inclusion of COPD orders in admission orders

Intervention Type: OTHER

Use of real-time data to identify a population of patients with COPD and prompt improved adherence to evidence-based guidelines through the automatic inclusion of a COPD order set in the admission orders.

Automatic inclusion and order set B

COPD order set is automatically included in admission orders as a dynamic and end user tested version.

Group Type: ACTIVE_COMPARATOR

Automatic inclusion of COPD orders in admission orders

Intervention Type: OTHER

Use of real-time data to identify a population of patients with COPD and prompt improved adherence to evidence-based guidelines through the automatic inclusion of a COPD order set in the admission orders.

Dynamic, end-user order set design

Intervention Type: OTHER

Use of a dynamic order set that has been end-user tested prior to launch rather than designed centrally by a committee to test use of order set components.

Interventions

Automatic inclusion of COPD orders in admission orders

Use of real-time data to identify a population of patients with COPD and prompt improved adherence to evidence-based guidelines through the automatic inclusion of a COPD order set in the admission orders.

Intervention Type: OTHER

Dynamic, end-user order set design

Use of a dynamic order set that has been end-user tested prior to launch rather than designed centrally by a committee to test use of order set components.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Patients 18 years old or greater admitted to the Hospital Medicine service at UCSF Medical Center who meet criteria as determined by predictive model to be likely admissions for COPD exacerbation.

Exclusion Criteria

• Patients admitted to other clinical services at UCSF Medical Center.

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

University of California, San Francisco

OTHER

Sponsor Role: lead

Responsible Party

Ari Hoffman

Assistant Clinical Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Ari Hoffman, MD

Role: PRINCIPAL_INVESTIGATOR

University of California, San Francisco

Locations

University of California, San Francisco

San Francisco, California, United States

Countries

United States

Other Identifiers

16-19504

Identifier Type: -

Identifier Source: org_study_id