Clinical Trial Details
— Status: Active, not recruiting
Administrative data
NCT number |
NCT04606849 |
Other study ID # |
1051464 |
Secondary ID |
|
Status |
Active, not recruiting |
Phase |
N/A
|
First received |
|
Last updated |
|
Start date |
November 12, 2020 |
Est. completion date |
September 30, 2023 |
Study information
Verified date |
February 2021 |
Source |
Intermountain Health Care, Inc. |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
Clinical Trial Summary
We plan to adapt an innovative, validated emergency department (ED) CDS tool based on
consensus guidelines for pneumonia care (ePNa) to function in urgent care clinics (Instacares
at Intermountain) and combine it seamlessly with Stanford's CheXED artificial intelligence
model using an interoperable platform currently under development by Care Transformation
Information Services at Intermountain. We will then deploy it to one of two groups of
Instacares (randomly selected) using the CFIR framework for Implementation Science best
practice.
Description:
Clinicians' ability to accurately diagnose pneumonia and then choose the most appropriate
treatment options is enhanced by well-designed clinical decision support (CDS). Pneumonia CDS
has historically been focused on inpatient settings, but ambulatory care settings with high
pneumonia patient volumes also might benefit. The investigators propose to adapt an
innovative, validated emergency department (ED) CDS tool based on consensus guidelines for
pneumonia care (ePNa) and deploy it to urgent care centers (UCC) using the CFIR framework.
Electronic tools such as ePNa may become even more useful within UCCs as the COVID-19
pandemic evolves, since recommendations can be readily updated as better methods of diagnosis
and effective treatment develop. ePNa within the ED has already been adapted to recommend
SARS-coV-2 testing for patients with pneumonia and signs and symptoms characteristic of viral
pneumonia.
The proposal supports four aims:
1. Adapt ePNa for UCC and after in silico testing, pilot it among "super user" clinicians
during UCC shifts and assess its usability. ePNa needs adaptation for more limited
patient data available in UCCs, calibration of severity measures for lower observed
mortality, and a chest imaging prompt in patients with pneumonia signs and symptoms.
ePNa for UCC will incorporate Stanford University's artificial intelligence CheXED model
to provide electronic classification of chest images in <10 seconds for elements of
pneumonia diagnosis and treatment (radiographic pneumonia, single vs multiple lobes, and
pleural effusion).
2. Using the CFIR framework, our prior ED implementation experience, a focus group of UCC
clinicians, semi-structured interviews, and direct observations of workflow including
ePNa guided transitions of care between clinicians, the investigators will identify
barriers and facilitators to adaptation and implementation of ePNa to UCCs.
3. Test the implementation strategy by deploying ePNa at one of two randomly chosen
Intermountain Healthcare UCC clusters each with about 800 annual pneumonia patients -
the other a usual care control.
4. Co-primary outcomes are a) accuracy of pneumonia diagnosis defined by compatible chief
complaint plus ≥ 1 pneumonia sign/symptom and radiographic confirmation will be ≥10%
higher in the ePNa cluster, and b) the percent of UCC pneumonia patients transferred to
an emergency department for further evaluation will decrease by ≥ 3% in the ePNa cluster
replaced by more direct hospital admissions or discharge home. Safety measures will be
unplanned subsequent 7-day ED visits/hospitalizations and 30-day mortality. Based on
this rigorous pilot study, the investigators anticipate a subsequent multi-system
cluster-randomized trial.
Our work incorporates the Five Rights of CDS to ensure that the strengths of this technology
are optimized in the clinical environment. The investigators will leverage experience in
innovative pneumonia research, pioneering CDS, and implementation science available at
Intermountain to successfully complete this proposal.