Adaptation and Pilot Implementation of ePNa Clinical Decision Support for Utah Urgent Care Clinics
Adaptation and Pilot Implementation of ePNa Clinical Decision Support for Utah Urgent Care Clinics
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.
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.
Inclusion Criteria:

 -  All patients ≥ 12 years of age with pneumonia: defined by the J-18.X pneumonia code or
 acute respiratory failure or sepsis with secondary pneumonia codes

 Survey All physicians and advanced practice clinicians who are employed and actively seeing
 patients in the 4 Utah Valley Instacares

 Exclusion Criteria:

 -  Patients without radiographic confirmation of pneumonia

 -  Subsequent episodes of pneumonia within 12 months (so as not to over-represent
 patients with recurrent pneumonia caused by recurrent aspiration or structural lung
 disease).

 Survey No providers will be excluded from the survey invitation