Your browser doesn't support javascript.
Automated Text-Based Symptom Monitoring With Rapid Clinician Triage for Patients With Cancer and Suspected or Confirmed COVID-19.
Cotner, Cody E; Balachandran, Mohan; Do, David; Ferrell, Will; Khan, Neda; Kopinsky, Michael; McGettigan, Suzanne; Morgan, Anna U; Zinck, Lindsey; Schuchter, Lynn M; Shulman, Lawrence N; Asch, David A; Manz, Christopher R; Parikh, Ravi B.
  • Cotner CE; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
  • Balachandran M; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA.
  • Do D; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
  • Ferrell W; Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
  • Khan N; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA.
  • Kopinsky M; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA.
  • McGettigan S; Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA.
  • Morgan AU; Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
  • Zinck L; Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA.
  • Schuchter LM; Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA.
  • Shulman LN; Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
  • Asch DA; Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA.
  • Manz CR; Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
  • Parikh RB; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA.
JCO Clin Cancer Inform ; 5: 1134-1140, 2021 10.
Article in English | MEDLINE | ID: covidwho-1518337
ABSTRACT

PURPOSE:

Patients with cancer are at greater risk of developing severe symptoms from COVID-19 than the general population. We developed and tested an automated text-based remote symptom-monitoring program to facilitate early detection of worsening symptoms and rapid assessment for patients with cancer and suspected or confirmed COVID-19.

METHODS:

We conducted a feasibility study of Cancer COVID Watch, an automated COVID-19 symptom-monitoring program with oncology nurse practitioner (NP)-led triage among patients with cancer between April 23 and June 30, 2020. Twenty-six patients with cancer and suspected or confirmed COVID-19 were enrolled. Enrolled patients received twice daily automated text messages over 14 days that asked "How are you feeling compared to 12 hours ago? Better, worse, or the same?" and, if worse, "Is it harder than usual for you to breathe?" Patients who responded worse and yes were contacted within 1 hour by an oncology NP.

RESULTS:

Mean age of patients was 62.5 years. Seventeen (65%) were female, 10 (38%) Black, and 15 (58%) White. Twenty-five (96%) patients responded to ≥ 1 symptom check-in, and overall response rate was 78%. Four (15%) patients were escalated to the triage line one was advised to present to the emergency department (ED), and three were managed in the outpatient setting. Median time from escalation to triage call was 11.5 minutes. Four (15%) patients presented to the ED without first escalating their care via our program. Participant satisfaction was high (Net Promoter Score 100, n = 4).

CONCLUSION:

Implementation of an intensive remote symptom monitoring and rapid NP triage program for outpatients with cancer and suspected or confirmed COVID-19 infection is possible. Similar tools may facilitate more rapid triage for patients with cancer in future pandemics.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Text Messaging / COVID-19 / Neoplasms Type of study: Diagnostic study / Prognostic study Limits: Female / Humans / Middle aged Language: English Journal: JCO Clin Cancer Inform Year: 2021 Document Type: Article Affiliation country: CCI.21.00069

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Text Messaging / COVID-19 / Neoplasms Type of study: Diagnostic study / Prognostic study Limits: Female / Humans / Middle aged Language: English Journal: JCO Clin Cancer Inform Year: 2021 Document Type: Article Affiliation country: CCI.21.00069