Predicting Favorable Outcomes in Hospitalized Covid-19 Patients
Last updated on July 2021Recruitment
- Recruitment Status
- Recruiting
- Estimated Enrollment
- 12000
Summary
- Conditions
- Adverse Event
- Corona Virus Infection
- COVID
- Type
- Interventional
- Phase
- Not Applicable
- Design
- Allocation: RandomizedIntervention Model: Parallel AssignmentIntervention Model Description: Display of risk score/ colored flag in Epic patient list column vs. no display ("missing"); will be viewable to all frontline workersMasking: Double (Participant, Outcomes Assessor)Masking Description: Participant and data analyst(s) are blindedPrimary Purpose: Health Services Research
Participation Requirements
- Age
- Between 18 years and 100 years
- Gender
- Both males and females
Description
To assess if display of low risk of adverse event in EPIC can safely reduce length of stay and plan for discharge.
To assess if display of low risk of adverse event in EPIC can safely reduce length of stay and plan for discharge.
Tracking Information
- NCT #
- NCT04570488
- Collaborators
- Not Provided
- Investigators
- Principal Investigator: Jonathan Austrian, MD NYU Langone Health
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