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Resource Savings Associated With Use of an Automated Symptom Monitoring Tool for COVID-19 Public Health Response, Summer 2020-Summer 2021
Active symptom monitoring is a key component of the public health response to COVID-19, but these activities are resource-intensive. Digital tools can help reduce the burden of staff time required for active symptom monitoring by automating routine outreach activities. PROGRAM: Sara Alert is an open...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health, Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532362/ https://www.ncbi.nlm.nih.gov/pubmed/36037463 http://dx.doi.org/10.1097/PHH.0000000000001552 |
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author | Sweeney, Kellen F. Halter, Heather M. Krell, Kerry McCormick, Donald Brown, Janet Simons, Aimee Santiago-Rosas, Christian J. Luna-Anavitate, Sylvianette Ramos-Colon, Miriam V. Marzán-Rodriguez, Melissa Bezold, Carla P. |
author_facet | Sweeney, Kellen F. Halter, Heather M. Krell, Kerry McCormick, Donald Brown, Janet Simons, Aimee Santiago-Rosas, Christian J. Luna-Anavitate, Sylvianette Ramos-Colon, Miriam V. Marzán-Rodriguez, Melissa Bezold, Carla P. |
author_sort | Sweeney, Kellen F. |
collection | PubMed |
description | Active symptom monitoring is a key component of the public health response to COVID-19, but these activities are resource-intensive. Digital tools can help reduce the burden of staff time required for active symptom monitoring by automating routine outreach activities. PROGRAM: Sara Alert is an open-source, Web-based automated symptom monitoring tool launched in April 2020 to support state, tribal, local, and territorial jurisdictions in their symptom monitoring efforts. IMPLEMENTATION: As of October 2021, a total of 23 public health jurisdictions in the United States had used Sara Alert to perform daily symptom monitoring for more than 6.1 million individuals. This analysis estimates staff time and cost saved in 3 jurisdictions that used Sara Alert as part of their COVID-19 response, across 2 use cases: monitoring of close contacts exposed to COVID-19 (Arkansas; Fairfax County, Virginia), and traveler monitoring (Puerto Rico). EVALUATION: A model-based approach was used to estimate the additional staff resources that would have been required to perform the active symptom monitoring automated by Sara Alert, if monitoring instead relied on traditional methods such as telephone outreach. Arkansas monitored 283 705 individuals over a 10-month study period, generating estimated savings of 61.9 to 100.6 full-time equivalent (FTE) staff, or $2 798 922 to $4 548 249. Fairfax County monitored 63 989 individuals over a 13-month study period, for an estimated savings of 24.8 to 41.4 FTEs, or $2 826 939 to $4 711 566. In Puerto Rico, where Sara Alert was used to monitor 2 631 306 travelers over the 11-month study period, estimated resource savings were 849 to 1698 FTEs, or $26 243 161 to $52 486 322. DISCUSSION: Automated symptom monitoring helped reduce the staff time required for active symptom monitoring activities. Jurisdictions reported that this efficiency supported a rapid and comprehensive COVID-19 response even when experiencing challenges with quickly scaling up their public health workforce. |
format | Online Article Text |
id | pubmed-9532362 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Wolters Kluwer Health, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95323622022-10-14 Resource Savings Associated With Use of an Automated Symptom Monitoring Tool for COVID-19 Public Health Response, Summer 2020-Summer 2021 Sweeney, Kellen F. Halter, Heather M. Krell, Kerry McCormick, Donald Brown, Janet Simons, Aimee Santiago-Rosas, Christian J. Luna-Anavitate, Sylvianette Ramos-Colon, Miriam V. Marzán-Rodriguez, Melissa Bezold, Carla P. J Public Health Manag Pract Research Reports Active symptom monitoring is a key component of the public health response to COVID-19, but these activities are resource-intensive. Digital tools can help reduce the burden of staff time required for active symptom monitoring by automating routine outreach activities. PROGRAM: Sara Alert is an open-source, Web-based automated symptom monitoring tool launched in April 2020 to support state, tribal, local, and territorial jurisdictions in their symptom monitoring efforts. IMPLEMENTATION: As of October 2021, a total of 23 public health jurisdictions in the United States had used Sara Alert to perform daily symptom monitoring for more than 6.1 million individuals. This analysis estimates staff time and cost saved in 3 jurisdictions that used Sara Alert as part of their COVID-19 response, across 2 use cases: monitoring of close contacts exposed to COVID-19 (Arkansas; Fairfax County, Virginia), and traveler monitoring (Puerto Rico). EVALUATION: A model-based approach was used to estimate the additional staff resources that would have been required to perform the active symptom monitoring automated by Sara Alert, if monitoring instead relied on traditional methods such as telephone outreach. Arkansas monitored 283 705 individuals over a 10-month study period, generating estimated savings of 61.9 to 100.6 full-time equivalent (FTE) staff, or $2 798 922 to $4 548 249. Fairfax County monitored 63 989 individuals over a 13-month study period, for an estimated savings of 24.8 to 41.4 FTEs, or $2 826 939 to $4 711 566. In Puerto Rico, where Sara Alert was used to monitor 2 631 306 travelers over the 11-month study period, estimated resource savings were 849 to 1698 FTEs, or $26 243 161 to $52 486 322. DISCUSSION: Automated symptom monitoring helped reduce the staff time required for active symptom monitoring activities. Jurisdictions reported that this efficiency supported a rapid and comprehensive COVID-19 response even when experiencing challenges with quickly scaling up their public health workforce. Wolters Kluwer Health, Inc. 2022-11 2022-08-27 /pmc/articles/PMC9532362/ /pubmed/36037463 http://dx.doi.org/10.1097/PHH.0000000000001552 Text en © 2022 Wolters Kluwer Health, Inc. All rights reserved. This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. |
spellingShingle | Research Reports Sweeney, Kellen F. Halter, Heather M. Krell, Kerry McCormick, Donald Brown, Janet Simons, Aimee Santiago-Rosas, Christian J. Luna-Anavitate, Sylvianette Ramos-Colon, Miriam V. Marzán-Rodriguez, Melissa Bezold, Carla P. Resource Savings Associated With Use of an Automated Symptom Monitoring Tool for COVID-19 Public Health Response, Summer 2020-Summer 2021 |
title | Resource Savings Associated With Use of an Automated Symptom Monitoring Tool for COVID-19 Public Health Response, Summer 2020-Summer 2021 |
title_full | Resource Savings Associated With Use of an Automated Symptom Monitoring Tool for COVID-19 Public Health Response, Summer 2020-Summer 2021 |
title_fullStr | Resource Savings Associated With Use of an Automated Symptom Monitoring Tool for COVID-19 Public Health Response, Summer 2020-Summer 2021 |
title_full_unstemmed | Resource Savings Associated With Use of an Automated Symptom Monitoring Tool for COVID-19 Public Health Response, Summer 2020-Summer 2021 |
title_short | Resource Savings Associated With Use of an Automated Symptom Monitoring Tool for COVID-19 Public Health Response, Summer 2020-Summer 2021 |
title_sort | resource savings associated with use of an automated symptom monitoring tool for covid-19 public health response, summer 2020-summer 2021 |
topic | Research Reports |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532362/ https://www.ncbi.nlm.nih.gov/pubmed/36037463 http://dx.doi.org/10.1097/PHH.0000000000001552 |
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