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| Name | Class |
|---|---|
| Stanford University | OTHER |
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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:
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Physician Survey | Other | A modified version of a previously validated REDCap questionnaire will be administered to Instacare clinicians in the cluster where ePNa-CheXED was deployed via email at 6 months after ePNa-CheXED implementation. Our questionnaire includes questions on respondent demographics and Likert-style questions about respondents' experiences with ePNa. We will validate our modified questionnaire by calculating component loadings and Cronbach Alphas (i.e., internal consistency) of Likert questions loading onto the same components |
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| Adapt ePNa-CheXED for InstaCares | Other | Adapt ePNa-CheXED for Instacares and after in silico testing, pilot it among "super user" clinicians during Instacare shifts and assess its usability. ePNa needs adaptation for more limited patient data available in Instacare clinics, calibration of severity measures for lower observed mortality, and a chest imaging prompt in patients with pneumonia signs and symptoms. ePNa-CheXED will incorporate Stanford University's artificial intelligence CheXED model to provide electronic classification of chest images in <1 second for elements of pneumonia diagnosis and treatment (radiographic pneumonia, single vs multiple lobes, and pleural effusion). |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Physician Survey | Other | Our questionnaire includes questions on respondent demographics and Likert-style questions about respondent experiences with ePNa. We will validate our modified questionnaire by calculating component loadings and Cronbach Alphas (i.e., internal consistency) of Likert questions loading onto the same components. |
| Measure | Description | Time Frame |
|---|---|---|
| ePNa utilization and impact on the UCC clinical environment | Frequency of clinicians' disagreement with different ePNa recommendations will be monitored along with a tally of the structured reasons for disagreement entered by clinicians into ePNa. | through study completion, year 3 of the study |
| Measure | Description | Time Frame |
|---|---|---|
| Number of unplanned subsequent ED Visits | within 7 days of initial encounter | |
| Number of unplanned hospitalizations | within 7 days of initial encounter | |
| Accuracy of pneumonia diagnosis given |
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Inclusion Criteria:
Survey All physicians and advanced practice clinicians who are employed and actively seeing patients in the 4 Utah Valley Instacares
Exclusion Criteria:
Survey No providers will be excluded from the survey invitation
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Valerie Aston | Contact | 801-507-4606 | valerie.aston@imail.org | |
| Carlos Barbagelata, MS | Contact | 801-507-4607 | carlos.barbagelata@imail.org |
| Name | Affiliation | Role |
|---|---|---|
| Nathan Dean, MD | Intermountain Health Care, Inc. | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| American Fork Instacare | Recruiting | American Fork | Utah | 84003 | United States |
In order to protect patient privacy and comply with relevant regulations, identified data will be unavailable. Requests for deidentified data from qualified researchers with appropriate ethics board approvals and relevant data use agreements will be processed by the Intermountain Office of Research, officeofresearch@imail.org
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| ePNa-CheXED | Device | ePNa-CheXED will incorporate Stanford University's artificial intelligence CheXED model to provide electronic classification of chest images in <1 second for elements of pneumonia diagnosis and treatment (radiographic pneumonia, single vs multiple lobes, and pleural effusion). |
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defined by compatible chief complaint (cough, dyspnea, chest pain, fever) plus . 1 pneumonia sign/symptom (temperature . 38.0C or < 36.0C, white blood cell count >10,000/ul or <4000/ul), bandemia >10%, SpO2<90% on room air, respiratory rate >20/minute)19 and radiographic confirmation |
| through study completion, year 3 of the study |
| The change in the transfer rate of UCC pneumonia patients to an ED | we want a decrease of . 3% in the ePNa cluster with those transfers replaced by direct hospital admissions or discharge home. | through study completion, year 3 of the study |
| Use of fewer health care resources | through study completion, year 3 of the study |
| Layton Instacare | Recruiting | Layton | Utah | 84041 | United States |
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| Lehi Instacare | Recruiting | Lehi | Utah | 84043 | United States |
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| Intermountain Medical Center | Not yet recruiting | Murray | Utah | 84107 | United States |
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| North Ogden Instacare | Not yet recruiting | North Ogden | Utah | 84414 | United States |
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| North Orem Instacare | Not yet recruiting | Orem | Utah | 84057 | United States |
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| Utah Valley Instacare | Recruiting | Provo | Utah | 84604 | United States |
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| Herefordshire Instacare | Not yet recruiting | Roy | Utah | 84067 | United States |
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| Saratoga Springs Instacare | Recruiting | Saratoga Springs | Utah | 84045 | United States |
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| South Ogden Instacare | Not yet recruiting | South Ogden | Utah | 84403 | United States |
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| Spanish Fork Instacare | Recruiting | Spanish Fork | Utah | 84660 | United States |
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| Springville Instacare | Not yet recruiting | Springville | Utah | 84663 | United States |
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| ID | Term |
|---|---|
| D011014 | Pneumonia |
| ID | Term |
|---|---|
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
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