Hospital length of stay throughout bed pathways and factors affecting this time: a non-concurrent cohort study of Colombia COVID-19 patients and an unCoVer network project

Abstract

Predictions of hospital beds occupancy depends on hospital admission rates and the length of stay (LoS) according to bed type (hospital and intensive care unit beds). The objective of this study was to describe the LoS of COVID-19 hospital patients in Colombia during 2020-2021. Accelerated failure time models were used to estimate the LoS distribution according to each bed type and throughout each bed pathway. Acceleration factors and 95% confidence intervals were calculated to measure the effect on LoS of the outcome, sex, age, admission period during the epidemic (i.e., epidemic waves, peaks or valleys, and before/after vaccination period), and patients’ geographic origin. Most of the admitted COVID-19 patients occupied just hospital bed. Recovered patients spent more time in the hospital and intensive care unit than deceased patients. Men had longer LoS than women. In general, the LoS increased with age. Finally, the LoS varied along epidemic waves. It was lower in epidemic valleys than peaks, and became shorter after vaccinations began in Colombia than before. Our study highlights the necessity of analyzing local data on hospital admission rates and LoS to design strategies to prioritize hospital beds resources during the current and future pandemics.

EpidemicKabu a new method to identify epidemic waves and their peaks and valleys

“…The study of epidemic waves is useful to predict the behavior of future waves (i.e., beginning, duration, and final) and therefore to predict the incidence of new cases [10,12]. It is also useful for retrospective analysis of epidemiological data, such as the estimation of the hospital length of stay through the waves of COVID-19 [15].…”