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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...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
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.
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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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