Mohammadreza Mirjalili; Mohammadreza Dehghani; Mehdi Raadabadi; Farzan Madadizadeh; Mohammad Sharifyazdi; Hosein Shojaefar; Masoud Sharifi; Mehdi Yavari; Ali Dehghani
Abstract
Background: Considering the high prevalence of COVID-19 in Iran, it is necessary to allocate health resources in response to this pandemic. Due to limitations in the number of hospital beds, analysis of the length of hospital stay in COVID-19 patients may be helpful for decision-making.Methods: This ...
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Background: Considering the high prevalence of COVID-19 in Iran, it is necessary to allocate health resources in response to this pandemic. Due to limitations in the number of hospital beds, analysis of the length of hospital stay in COVID-19 patients may be helpful for decision-making.Methods: This retrospective cohort study (survival study) was conducted through a follow-up of 1465 COVID-19 patients in Yazd Province, Iran. Demographic, diagnostic, and clinical data were collected using the COVID-19 data dashboard of Shahid Sadoughi University of Medical Sciences. The Kaplan-Meier method and Cox regression were used to calculate the survival probability and hazard ratio; the log-rank test was applied to compare survival function according to qualitative variables.Results: The median and mean survival time was 25 days (95% CI: 19.10-30.89 days) and 28.38 days (95% CI: 25.6-31.16 days), respectively. The Survival probability for one week, two weeks, three weeks, four weeks, five weeks, six weeks, and seven weeks and more was 92%, 76%, 57%, 48%, 45%, 33%, and 20%, respectively. There was a significant relationship between survival time and age categories, CT scan results, history of chronic pulmonary disease, history of diabetes, history of cardiovascular disease, and disease severity (P<0.05).Conclusion: According to the results, age, history of cardiovascular and pulmonary diseases, and history of diabetes increased the length of hospital stay. Preventive measures should be followed to prevent COVID-19 infection and manage hospital beds required for efficient treatment of patients.
Sima Rafiei; Ahad Alizadeh; Rohollah Kalhor; Aidin Aryankhesal; Ahmad Ghashghaee
Abstract
Background: The pandemic of COVID-19 affect all healthcare systems globally, and its effect on different hospital performance indicators has been debated. The study aimed to compare the impacts of COVID-19 on hospital performance indicators using pre-and post-pandemic data from training hospitals.Methods: ...
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Background: The pandemic of COVID-19 affect all healthcare systems globally, and its effect on different hospital performance indicators has been debated. The study aimed to compare the impacts of COVID-19 on hospital performance indicators using pre-and post-pandemic data from training hospitals.Methods: We conducted an observational cohort study of hospital performance indicators from two healthcare facilities affiliated with Qazvin University of Medical Sciences in the north-west of Iran. The R statistical software was used to analyze monthly data on three basic performance indicators, including bed turnover, average length of stay (LOS), and bed occupancy rate before and during the outbreak of Coronavirus disease-19 (COVID-19).Results: The pandemic had a remarkable effect on the level of bed turnover, the average length of stay (LOS), and the bed occupancy rate after one month from the COVID-19 outbreak (P<0.05). Moreover, regression results showed that after the pandemic, the first two mentioned indicators increased monthly at 108.18 and 0.15, respectively, while LOS decreased by 0.09 monthly (P<0.05).Conclusion: Based on the study findings, a significant decline in hospital occupancy rate and bed turnover was observed after one month since the beginning of the outbreak. This reduction was associated with a longer LOS. Using ITS in pandemics such as COVID-19 can evaluate the effect of various policies on outcome measures and help policymakers make effective decisions.