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Patient Flow Dynamics in Hospital Systems During Times of COVID-19: Cox Proportional Hazard Regression Analysis
Objectives: The present study is aimed at estimating patient flow dynamic parameters and requirement for hospital beds. Second, the effects of age and gender on parameters were evaluated. Patients and Methods: In this retrospective cohort study, 987 COVID-19 patients were enrolled from SMS Medical C...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7793894/ https://www.ncbi.nlm.nih.gov/pubmed/33425835 http://dx.doi.org/10.3389/fpubh.2020.585850 |
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author | Bhandari, Sudhir Tak, Amit Singhal, Sanjay Shukla, Jyotsna Shaktawat, Ajit Singh Gupta, Jitendra Patel, Bhoopendra Kakkar, Shivankan Dube, Amitabh Dia, Sunita Dia, Mahendra Wehner, Todd C. |
author_facet | Bhandari, Sudhir Tak, Amit Singhal, Sanjay Shukla, Jyotsna Shaktawat, Ajit Singh Gupta, Jitendra Patel, Bhoopendra Kakkar, Shivankan Dube, Amitabh Dia, Sunita Dia, Mahendra Wehner, Todd C. |
author_sort | Bhandari, Sudhir |
collection | PubMed |
description | Objectives: The present study is aimed at estimating patient flow dynamic parameters and requirement for hospital beds. Second, the effects of age and gender on parameters were evaluated. Patients and Methods: In this retrospective cohort study, 987 COVID-19 patients were enrolled from SMS Medical College, Jaipur (Rajasthan, India). The survival analysis was carried out from February 29 through May 19, 2020, for two hazards: Hazard 1 was hospital discharge, and Hazard 2 was hospital death. The starting point for survival analysis of the two hazards was considered to be hospital admission. The survival curves were estimated and additional effects of age and gender were evaluated using Cox proportional hazard regression analysis. Results: The Kaplan Meier estimates of lengths of hospital stay (median = 10 days, IQR = 5–15 days) and median survival rate (more than 60 days due to a large amount of censored data) were obtained. The Cox model for Hazard 1 showed no significant effect of age and gender on duration of hospital stay. Similarly, the Cox model 2 showed no significant difference of age and gender on survival rate. The case fatality rate of 8.1%, recovery rate of 78.8%, mortality rate of 0.10 per 100 person-days, and hospital admission rate of 0.35 per 100,000 person-days were estimated. Conclusion: The study estimates hospital bed requirements based on median length of hospital stay and hospital admission rate. Furthermore, the study concludes there are no effects of age and gender on average length of hospital stay and no effects of age and gender on survival time in above-60 age groups. |
format | Online Article Text |
id | pubmed-7793894 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77938942021-01-09 Patient Flow Dynamics in Hospital Systems During Times of COVID-19: Cox Proportional Hazard Regression Analysis Bhandari, Sudhir Tak, Amit Singhal, Sanjay Shukla, Jyotsna Shaktawat, Ajit Singh Gupta, Jitendra Patel, Bhoopendra Kakkar, Shivankan Dube, Amitabh Dia, Sunita Dia, Mahendra Wehner, Todd C. Front Public Health Public Health Objectives: The present study is aimed at estimating patient flow dynamic parameters and requirement for hospital beds. Second, the effects of age and gender on parameters were evaluated. Patients and Methods: In this retrospective cohort study, 987 COVID-19 patients were enrolled from SMS Medical College, Jaipur (Rajasthan, India). The survival analysis was carried out from February 29 through May 19, 2020, for two hazards: Hazard 1 was hospital discharge, and Hazard 2 was hospital death. The starting point for survival analysis of the two hazards was considered to be hospital admission. The survival curves were estimated and additional effects of age and gender were evaluated using Cox proportional hazard regression analysis. Results: The Kaplan Meier estimates of lengths of hospital stay (median = 10 days, IQR = 5–15 days) and median survival rate (more than 60 days due to a large amount of censored data) were obtained. The Cox model for Hazard 1 showed no significant effect of age and gender on duration of hospital stay. Similarly, the Cox model 2 showed no significant difference of age and gender on survival rate. The case fatality rate of 8.1%, recovery rate of 78.8%, mortality rate of 0.10 per 100 person-days, and hospital admission rate of 0.35 per 100,000 person-days were estimated. Conclusion: The study estimates hospital bed requirements based on median length of hospital stay and hospital admission rate. Furthermore, the study concludes there are no effects of age and gender on average length of hospital stay and no effects of age and gender on survival time in above-60 age groups. Frontiers Media S.A. 2020-12-08 /pmc/articles/PMC7793894/ /pubmed/33425835 http://dx.doi.org/10.3389/fpubh.2020.585850 Text en Copyright © 2020 Bhandari, Tak, Singhal, Shukla, Shaktawat, Gupta, Patel, Kakkar, Dube, Dia, Dia and Wehner. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Bhandari, Sudhir Tak, Amit Singhal, Sanjay Shukla, Jyotsna Shaktawat, Ajit Singh Gupta, Jitendra Patel, Bhoopendra Kakkar, Shivankan Dube, Amitabh Dia, Sunita Dia, Mahendra Wehner, Todd C. Patient Flow Dynamics in Hospital Systems During Times of COVID-19: Cox Proportional Hazard Regression Analysis |
title | Patient Flow Dynamics in Hospital Systems During Times of COVID-19: Cox Proportional Hazard Regression Analysis |
title_full | Patient Flow Dynamics in Hospital Systems During Times of COVID-19: Cox Proportional Hazard Regression Analysis |
title_fullStr | Patient Flow Dynamics in Hospital Systems During Times of COVID-19: Cox Proportional Hazard Regression Analysis |
title_full_unstemmed | Patient Flow Dynamics in Hospital Systems During Times of COVID-19: Cox Proportional Hazard Regression Analysis |
title_short | Patient Flow Dynamics in Hospital Systems During Times of COVID-19: Cox Proportional Hazard Regression Analysis |
title_sort | patient flow dynamics in hospital systems during times of covid-19: cox proportional hazard regression analysis |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7793894/ https://www.ncbi.nlm.nih.gov/pubmed/33425835 http://dx.doi.org/10.3389/fpubh.2020.585850 |
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