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From Testing to Decision-Making: A Data-Driven Analytics COVID-19 Response
In March 2020, NorthShore University Health System laboratories mobilized to develop and validate polymerase chain reaction based testing for detection of SARS-CoV-2. Using laboratory data, NorthShore University Health System created the Data Coronavirus Analytics Research Team to track activities a...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060741/ https://www.ncbi.nlm.nih.gov/pubmed/33959677 http://dx.doi.org/10.1177/23742895211010257 |
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author | Konchak, Chad W. Krive, Jacob Au, Loretta Chertok, Daniel Dugad, Priya Granchalek, Gus Livschiz, Ekaterina Mandala, Rupesh McElvania, Erin Park, Christine Robicsek, Ari Sabatini, Linda M. Shah, Nirav S. Kaul, Karen |
author_facet | Konchak, Chad W. Krive, Jacob Au, Loretta Chertok, Daniel Dugad, Priya Granchalek, Gus Livschiz, Ekaterina Mandala, Rupesh McElvania, Erin Park, Christine Robicsek, Ari Sabatini, Linda M. Shah, Nirav S. Kaul, Karen |
author_sort | Konchak, Chad W. |
collection | PubMed |
description | In March 2020, NorthShore University Health System laboratories mobilized to develop and validate polymerase chain reaction based testing for detection of SARS-CoV-2. Using laboratory data, NorthShore University Health System created the Data Coronavirus Analytics Research Team to track activities affected by SARS-CoV-2 across the organization. Operational leaders used data insights and predictions from Data Coronavirus Analytics Research Team to redeploy critical care resources across the hospital system, and real-time data were used daily to make adjustments to staffing and supply decisions. Geographical data were used to triage patients to other hospitals in our system when COVID-19 detected pavilions were at capacity. Additionally, one of the consequences of COVID-19 was the inability for patients to receive elective care leading to extended periods of pain and uncertainty about a disease or treatment. After shutting down elective surgeries beginning in March of 2020, NorthShore University Health System set a recovery goal to achieve 80% of our historical volumes by October 1, 2020. Using the Data Coronavirus Analytics Research Team, our operational and clinical teams were able to achieve 89% of our historical volumes a month ahead of schedule, allowing rapid recovery of surgical volume and financial stability. The Data Coronavirus Analytics Research Team also was used to demonstrate that the accelerated recovery period had no negative impact with regard to iatrogenic COVID-19 infection and did not result in increased deep vein thrombosis, pulmonary embolisms, or cerebrovascular accident. These achievements demonstrate how a coordinated and transparent data-driven effort that was built upon a robust laboratory testing capability was essential to the operational response and recovery from the COVID-19 crisis. |
format | Online Article Text |
id | pubmed-8060741 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-80607412021-05-05 From Testing to Decision-Making: A Data-Driven Analytics COVID-19 Response Konchak, Chad W. Krive, Jacob Au, Loretta Chertok, Daniel Dugad, Priya Granchalek, Gus Livschiz, Ekaterina Mandala, Rupesh McElvania, Erin Park, Christine Robicsek, Ari Sabatini, Linda M. Shah, Nirav S. Kaul, Karen Acad Pathol Special Collection: COVID-19 In March 2020, NorthShore University Health System laboratories mobilized to develop and validate polymerase chain reaction based testing for detection of SARS-CoV-2. Using laboratory data, NorthShore University Health System created the Data Coronavirus Analytics Research Team to track activities affected by SARS-CoV-2 across the organization. Operational leaders used data insights and predictions from Data Coronavirus Analytics Research Team to redeploy critical care resources across the hospital system, and real-time data were used daily to make adjustments to staffing and supply decisions. Geographical data were used to triage patients to other hospitals in our system when COVID-19 detected pavilions were at capacity. Additionally, one of the consequences of COVID-19 was the inability for patients to receive elective care leading to extended periods of pain and uncertainty about a disease or treatment. After shutting down elective surgeries beginning in March of 2020, NorthShore University Health System set a recovery goal to achieve 80% of our historical volumes by October 1, 2020. Using the Data Coronavirus Analytics Research Team, our operational and clinical teams were able to achieve 89% of our historical volumes a month ahead of schedule, allowing rapid recovery of surgical volume and financial stability. The Data Coronavirus Analytics Research Team also was used to demonstrate that the accelerated recovery period had no negative impact with regard to iatrogenic COVID-19 infection and did not result in increased deep vein thrombosis, pulmonary embolisms, or cerebrovascular accident. These achievements demonstrate how a coordinated and transparent data-driven effort that was built upon a robust laboratory testing capability was essential to the operational response and recovery from the COVID-19 crisis. SAGE Publications 2021-04-20 /pmc/articles/PMC8060741/ /pubmed/33959677 http://dx.doi.org/10.1177/23742895211010257 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Special Collection: COVID-19 Konchak, Chad W. Krive, Jacob Au, Loretta Chertok, Daniel Dugad, Priya Granchalek, Gus Livschiz, Ekaterina Mandala, Rupesh McElvania, Erin Park, Christine Robicsek, Ari Sabatini, Linda M. Shah, Nirav S. Kaul, Karen From Testing to Decision-Making: A Data-Driven Analytics COVID-19 Response |
title | From Testing to Decision-Making: A Data-Driven Analytics COVID-19
Response |
title_full | From Testing to Decision-Making: A Data-Driven Analytics COVID-19
Response |
title_fullStr | From Testing to Decision-Making: A Data-Driven Analytics COVID-19
Response |
title_full_unstemmed | From Testing to Decision-Making: A Data-Driven Analytics COVID-19
Response |
title_short | From Testing to Decision-Making: A Data-Driven Analytics COVID-19
Response |
title_sort | from testing to decision-making: a data-driven analytics covid-19
response |
topic | Special Collection: COVID-19 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060741/ https://www.ncbi.nlm.nih.gov/pubmed/33959677 http://dx.doi.org/10.1177/23742895211010257 |
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