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. 2023 Feb 20;11(4):627.
doi: 10.3390/healthcare11040627.

Time-to-Event Analysis of Factors Influencing Delay in Discharge from a Subacute Complex Discharge Unit during the First Year of the Pandemic (2020) in an Irish Tertiary Centre Hospital

Nithya Rajendran  1 , Puteri Maisarah Rameli  1 , Keneilwe Malomo  2 , Declan Byrne  2 , Joseph Browne  2 , Ontefetse Ntlholang  2
Affiliations

Time-to-Event Analysis of Factors Influencing Delay in Discharge from a Subacute Complex Discharge Unit during the First Year of the Pandemic (2020) in an Irish Tertiary Centre Hospital

Nithya Rajendran et al. Healthcare (Basel). .

Abstract

Our study aimed to analyse delaying factors amongst patients with a length of stay (LOS) > 15 days during the COVID-19 pandemic using time-to-event analysis. A total of 390 patients were admitted between March 2020-February 2021 to the subacute complex discharge unit in St James's Hospital: 326 (83.6%) were >65 years of age and 233 (59.7%) were female. The median (IQR) age was 79 (70-86) years with a median (IQR) of 19.4 (10-41) days. A total of 237 (60.7%) events were uncensored, with LOS > 15 days, of which 138 (58.2%) were female and 124 (52.32%) had >4 comorbidities; 153 (39.2%) were censored into LOS ≤ 15 days, and death occurred in 19 (4.8%). Kaplan-Meier's plot compared factors causing a delay in discharge to the single factors: age, gender, and multimorbidity. A multivariate Cox regression analysis adjusted to age, gender, and multimorbidity predicted factors affecting LOS. Further research is required to explore multimorbidity as a risk factor for mortality in patients with prolonged LOS within a complex discharge unit and target gender-specific frailty measures to achieve high-quality patient management.

Keywords: COVID-19; Cox regression analysis; Kaplan–Meier analysis; complex discharge unit; delayed transfers of care; discharge delay; length of stay; pandemic; time-to-event analysis.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Kaplan–Meier curves for (A) age, (B) gender, (C) multimorbidity, (D) complications arising from primary diagnoses, (E) healthcare-associated infections, (F) frailty or falls necessitating integrated rehabilitation, (G) patient-centred needs, (H) community services contributing to delays in discharge during the first year of the pandemic in complex discharge unit. Figure legend: Each figure exhibits the overall delay in the length of stay (LOS) in number of days, with the numbers of patients at risk respectively below the curve.
Figure 1
Figure 1
Kaplan–Meier curves for (A) age, (B) gender, (C) multimorbidity, (D) complications arising from primary diagnoses, (E) healthcare-associated infections, (F) frailty or falls necessitating integrated rehabilitation, (G) patient-centred needs, (H) community services contributing to delays in discharge during the first year of the pandemic in complex discharge unit. Figure legend: Each figure exhibits the overall delay in the length of stay (LOS) in number of days, with the numbers of patients at risk respectively below the curve.
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