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Using Virtual Care to Facilitate Direct Hospital Admissions in Outpatients with Worsening COVID-19 Infection.
Lam, Philip W; Andany, Nisha; Chan, Adrienne K; Stroud, Lynfa; Shadowitz, Steven; Daneman, Nick.
  • Lam PW; Division of Infectious Diseases, Sunnybrook Health Sciences Centre, Toronto, Canada.
  • Andany N; Department of Medicine, University of Toronto, Toronto, Canada.
  • Chan AK; Division of Infectious Diseases, Sunnybrook Health Sciences Centre, Toronto, Canada.
  • Stroud L; Department of Medicine, University of Toronto, Toronto, Canada.
  • Shadowitz S; Division of Infectious Diseases, Sunnybrook Health Sciences Centre, Toronto, Canada.
  • Daneman N; Department of Medicine, University of Toronto, Toronto, Canada.
Telemed J E Health ; 2022 Mar 30.
Article in English | MEDLINE | ID: covidwho-2107324
ABSTRACT
Recognizing emergency department overcrowding during the COVID-19 pandemic, a pathway to facilitate direct admissions for outpatients with worsening COVID-19 infection was created using the COVID-19 expansion to outpatients (COVIDEO) virtual care program. Outpatients appropriate for direct admission had oxygen saturations consistently <92% without severe respiratory distress. Pulse oximeters were proactively delivered to high-risk patients, and patients contacted the program in the event of worsening symptoms or desaturation persistently <92%. Over a 15-month period, 9,116 outpatients were managed by the program, 164 of whom were hospitalized, and 83 of those hospitalized (50.6%) were directly admitted through this pathway. Of those directly admitted, 10 (12.0%) patients required ICU admission, occurring a median of 4 days from hospital admission. The mortality rate among directly admitted patients was 3.6% (3/83). Implementation of a virtual care program to facilitate direct admissions in outpatients with COVID-19 created a safe, efficient, and patient-centered pathway of care.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Long Covid Language: English Journal subject: Medical Informatics / Health Services Year: 2022 Document Type: Article Affiliation country: Tmj.2021.0640

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Long Covid Language: English Journal subject: Medical Informatics / Health Services Year: 2022 Document Type: Article Affiliation country: Tmj.2021.0640