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Testing use of predictive analytics to predict which COVID-19+ patients are at low risk for an adverse event (ICU transfer, intubation, mortality, hospice discharge, re-presentation to the ED, oxygen requirements exceeding nasal cannula at 6L/Min) in the next 96 hours
To assess if display of low risk of adverse event in EPIC can safely reduce length of stay and plan for discharge.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Quality improvement - Display | Display of risk score/ colored flag in Epic patient list column; will be viewable to all frontline workers |
| |
| No Display | No display ("hidden") of risk score/ colored flag in Epic patient list column; not viewable to all frontline workers |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| EPIC risk score display | Other | Display of risk score/ colored flag in Epic patient list column |
|
| Measure | Description | Time Frame |
|---|---|---|
| Reduction in days from first low-risk score to discharge | Reduction in days from first low-risk score to discharge | 96 Hours |
| Measure | Description | Time Frame |
|---|---|---|
| Reduction in length of stay (LOS) | Reduction in LOS for green patients that have not been in the ICU | 96 hours |
| Reduction in GTD vs. LOS | Reduction in GTD vs. LOS for all green patients discharged alive vs all patients discharged alive |
| Measure | Description | Time Frame |
|---|---|---|
| Re-presentation to ED | 96 hours | |
| Readmission to hospital | 96 hours | |
| Mortality |
Inclusion Criteria: Adult hospitalized COVID19+ patients predicted to have no adverse event at 96 events with a threshold at 90% PPV, with at least one low risk during their admission who are discharged alive and have not been in the ICU
Exclusion Criteria: Age < 18 years not hospitalized for COVID19+.
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Adult hospitalized COVID19+ patients predicted to have no adverse event at 96 events with a threshold at 90% PPV, with at least one low risk during their admission who are discharged alive and have not been in the ICU
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| Name | Affiliation | Role |
|---|---|---|
| Jonathan Austrian, MD | NYU Langone Health | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| NYU Langone Health | New York | New York | 10016 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35896506 | Derived | Major VJ, Jones SA, Razavian N, Bagheri A, Mendoza F, Stadelman J, Horwitz LI, Austrian J, Aphinyanaphongs Y. Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial. Appl Clin Inform. 2022 May;13(3):632-640. doi: 10.1055/s-0042-1750416. Epub 2022 Jul 27. |
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| ID | Term |
|---|---|
| D018352 | Coronavirus Infections |
| ID | Term |
|---|---|
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D014777 | Virus Diseases |
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| 96 hours |
| No change in 30 day re-ED presentation or hospital admission rate for cohort | No change in 30 day re-ED presentation or hospital admission rate for cohort | 96 hours |
| 96 hours |
| Postdischarge mortality | 96 hours |
| D007239 |
| Infections |