Assessing the performance indicators of hospitals before and after the pandemic of COVID-19: A time series study from January 2019 to December 2021

Sima Rafiei, Ahad Alizadeh, Rohollah Kalhor, Aidin Aryankhesal, Ahmad Ghashghaee

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)649-656
Number of pages8
JournalJournal of Health Sciences and Surveillance System
Publication statusPublished - Jul 2023


  • Bed occupancy rate
  • Bed turnover
  • COVID-19 pandemic
  • Interrupted time series
  • Length of stay

Cite this