Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic
INTRODUCTION: SARS CoV-2 pandemic is pressing hard on the responsiveness of health systems worldwide, notably concerning the massive surge in demand for intensive care hospital beds.
AIM: This study proposes a methodology to estimate the saturation moment of hospital intensive care beds (critical care beds) and determine the number of units required to compensate for this saturation.
METHODS: A total of 22,016 patients with diagnostic confirmation for COVID-19 caused by SARS-CoV-2 were analyzed between March 4 and May 5, 2020, nationwide. Based on information from the Chilean Ministry of Health and ministerial announcements in the media, the overall availability of critical care beds was estimated at 1,900 to 2,000. The Gompertz function was used to estimate the expected number of COVID-19 patients and to assess their exposure to the available supply of intensive care beds in various possible scenarios, taking into account the supply of total critical care beds, the average occupational index, and the demand for COVID-19 patients who would require an intensive care bed.
RESULTS: A 100% occupancy of critical care beds could be reached between May 11 and May 27. This condition could be extended for around 48 days, depending on how the expected over-demand is managed.
CONCLUSION: A simple, easily interpretable, and applicable to all levels (nationwide, regionwide, municipalities, and hospitals) model is offered as a contribution to managing the expected demand for the coming weeks and helping reduce the adverse effects of the COVID-19 pandemic.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2020 |
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Erschienen: |
2020 |
Enthalten in: |
Zur Gesamtaufnahme - volume:20 |
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Enthalten in: |
Medwave - 20(2020), 9 vom: 05. Okt., Seite e8039 |
Sprache: |
Spanisch |
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Weiterer Titel: |
Modelamiento predictivo para el cálculo de demanda de camas hospitalarias de cuidados intensivos a nivel nacional en el marco de la pandemia por COVID-19 |
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Beteiligte Personen: |
Peña, Víctor Hugo [VerfasserIn] |
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Links: |
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Themen: |
2019 novel coronavirus disease |
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Anmerkungen: |
Date Completed 22.10.2020 Date Revised 17.04.2022 published: Electronic Citation Status MEDLINE |
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doi: |
10.5867/medwave.2020.09.8039 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM31601415X |
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245 | 1 | 0 | |a Predictive modeling to estimate the demand for intensive care hospital beds nationwide in the context of the COVID-19 pandemic |
246 | 3 | 3 | |a Modelamiento predictivo para el cálculo de demanda de camas hospitalarias de cuidados intensivos a nivel nacional en el marco de la pandemia por COVID-19 |
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520 | |a INTRODUCTION: SARS CoV-2 pandemic is pressing hard on the responsiveness of health systems worldwide, notably concerning the massive surge in demand for intensive care hospital beds | ||
520 | |a AIM: This study proposes a methodology to estimate the saturation moment of hospital intensive care beds (critical care beds) and determine the number of units required to compensate for this saturation | ||
520 | |a METHODS: A total of 22,016 patients with diagnostic confirmation for COVID-19 caused by SARS-CoV-2 were analyzed between March 4 and May 5, 2020, nationwide. Based on information from the Chilean Ministry of Health and ministerial announcements in the media, the overall availability of critical care beds was estimated at 1,900 to 2,000. The Gompertz function was used to estimate the expected number of COVID-19 patients and to assess their exposure to the available supply of intensive care beds in various possible scenarios, taking into account the supply of total critical care beds, the average occupational index, and the demand for COVID-19 patients who would require an intensive care bed | ||
520 | |a RESULTS: A 100% occupancy of critical care beds could be reached between May 11 and May 27. This condition could be extended for around 48 days, depending on how the expected over-demand is managed | ||
520 | |a CONCLUSION: A simple, easily interpretable, and applicable to all levels (nationwide, regionwide, municipalities, and hospitals) model is offered as a contribution to managing the expected demand for the coming weeks and helping reduce the adverse effects of the COVID-19 pandemic | ||
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