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Outcomes following admission to intensive care units (ICU) may vary with time and day. This study investigated associations between time of day and risk of ICU mortality and chance of ICU discharge in acute ICU admissions. Adult patients (age ≥ 18 years) who were admitted to ICUs participating in the Austrian intensive care database due to medical...
Citations
... Physical and emotional exhaustion negatively impacted the quality of the work-life balance of healthcare providers due to increased work demands, shift overload, and the risk of infection for themselves and their families during the pandemic [10][11] . Previous ICU studies attempted to identify the 'time effect', 'off-hour effect' or the 'weekend effect' on mortality; however, the conflicting results prevented a definitive conclusion [12][13][14][15] . A multicenter prospective study revealed that the most patients died at night or on weekends (58%), and that 64% of these deaths were unexpected 16 . ...
Background
Coronavirus disease 2019 (COVID-19) disrupted standard health policies and routine medical care, and thus, the management andtreatment pathways of many clinical conditions have changed as never before. The negative impact of the pandemic rendered thesystemic disease more complicated and accelerated mortality. For the last two years, clinicians have primarily focused on COVID-19patients; however, the non-COVID-19 critically ill patients needed to be addressed from multiple perspectives. This study investigatedthe demographic and clinical characteristics of non-COVID-19 critical care patients admitted concurrently with a COVID-19 wave.The objective of this study was to identify the risk factors for mortality in critically ill non-COVID-19 patients.Methods
All consecutive cases admitted to the intensive care unit (ICU) were included in the study between January 1, 2021 and July 14, 2021.All data, including age, gender, admission characteristics, patient dependency, pre-existing systemic diseases, the severity of illness(Acute Physiology and Chronic Health Evaluation –APACHE-II), predicted death rate in ICU, life-sustaining medical procedures onadmission or during ICU stay, length of stay, and admission time to the ICU, were obtained from the hospital’s electronic database. TheCharlson Comorbidity Index (CCI) was assessed for all patients.ResultsA total of 192 patients were screened during the study period. Mortality was significantly increased in non-surgical patients, previouslydependent patients, patients requiring mechanical ventilation, continuous renal replacement therapy, and patients requiring the infusionof vasoactive medications. The number of pre-existing diseases and the admission time had no impact on mortality. The mean CCIwas significantly higher in non-survivors but was not a strong predictor of mortality as APACHE II.Conclusions
In this retrospective study, the severity of illness and the need for vasoactive agent infusion were significantly higher in non-survivorsconfirmed by multivariate analysis as predictive factors for mortality in critical non-COVID-19 patients.
... 18,21 Transfer time of day captured differences in staffing resources between daytime hours (Monday through Friday, 7:00 AM-7:00 PM) and nights and weekends that impact resources for appropriately escalating patients. [22][23][24] Patients with ET were matched with non-ET controls in a ratio of 1:3, nearest neighbor method, and caliper equal to 0.02. Cases and control characteristics were compared postmatch to ensure balance. ...
OBJECTIVES
Emergency transfers (ETs), deterioration events with late recognition requiring ICU interventions within 1 hour of transfer, are associated with adverse outcomes. We leveraged electronic health record (EHR) data to assess the association between ETs and outcomes. We also evaluated the association between intervention timing (urgency) and outcomes.
METHODS
We conducted a propensity-score-matched study of hospitalized children requiring ICU transfer between 2015 and 2019 at a single institution. The primary exposure was ET, automatically classified using Epic Clarity Data stored in our enterprise data warehouse endotracheal tube in lines/drains/airway flowsheet, vasopressor in medication administration record, and/or ≥60 ml/kg intravenous fluids in intake/output flowsheets recorded within 1 hour of transfer. Urgent intervention was defined as interventions within 12 hours of transfer.
RESULTS
Of 2037 index transfers, 129 (6.3%) met ET criteria. In the propensity-score-matched cohort (127 ET, 374 matched controls), ET was associated with higher in-hospital mortality (13% vs 6.1%; odds ratio, 2.47; 95% confidence interval [95% CI], 1.24–4.9, P = .01), longer ICU length of stay (subdistribution hazard ratio of ICU discharge 0.74; 95% CI, 0.61–0.91, P < .01), and longer posttransfer length of stay (SHR of hospital discharge 0.71; 95% CI, 0.56–0.90, P < .01). Increased intervention urgency was associated with increased mortality risk: 4.1% no intervention, 6.4% urgent intervention, and 10% emergent intervention.
CONCLUSIONS
An EHR measure of deterioration with late recognition is associated with increased mortality and length of stay. Mortality risk increased with intervention urgency. Leveraging EHR automation facilitates generalizability, multicenter collaboratives, and metric consistency.
... Few older studies (von Jenny, 1933;Smolensky et al., 1972;Reinberg et al., 1973;Mitler et al., 1987) have reported a peak mortality between 6am to 8am wherein the source of data was death certificates; with some explanations proposed for such pattern. A recent study (Zajic et al., 2019) has reported "time effects" in Intensive Care Units (ICUs) wherein the Hazard Rate was found to decrease over the day. We therefore decided to assess whether such a time dependent pattern exists in ICUs of our institution, and if so, to find the reasons behind the same. ...
... Further, 24-hour day was divided into 6 intervals of 4 hours, each labeled as group A to F (i.e. A: 12 midnight to 3.59am, B: 4am to 7.59am … and so on) similar to that done by Zajic et al. (Zajic et al., 2019) All patient deaths were categorized into each of these groups based on the time of death. The null hypothesis (H2 o ) was formulated as: "There is no statistically significant difference in rate of deaths in each of these six time-intervals." ...
The study intends to ascertain whether higher patient mortality occurs during weekends or nighttime or during a specific time of day. Time of death of all deceased in ICUs of a teaching hospital during study period (n = 844) was noted and analyzed. It was found that compared to daytime working hours, significantly higher mortality is not observed during Off Duty Hours (i.e. Evening/Night/Weekends/Holidays) and has no relationship with any particular time of the day. Patient deaths over time were found to conform to Poisson distribution. ICU deaths occur randomly and independently with no effect of nighttime/weekend or particular time of day.
... 16 For patients with multiple ICU admissions, only the rst admission was analyzed. The included ICUs were nine mixed medical/surgical units with a median [IQR] of 24 [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] beds. Two units were classi ed as academic/quaternary, two were academic/tertiary units, and ve were community/metropolitan units (Table 1). ...
... The afterhours ICU discharge of patients appears to be an omnipresent practice, occurring with greater frequently in our large Canadian health region than described in other jurisdictions [6][7][8][9][10]12,15 and exhibiting an increasing trend over time. 5,27 Afterhours discharges would appear predominantly driven by trends in larger academic/tertiary hospitals. This practice would be acceptable to patients, their families and healthcare professionals provided it is organized, planned and proven safe 1 ; however, this is not supported by evidence. ...
Background: There is conflicting evidence on the association between afterhours discharge from the intensive care unit (ICU) and hospital mortality. We examined the effects of afterhours discharge, including the potential effect of residual organ dysfunction, on hospital mortality in a large integrated health region.
Methods: We performed a multi-centre retrospective cohort study of 10,463 adults discharged from nine mixed medical/surgical ICUs in Alberta from June 2012 to December 2014. We applied a two-stage modelling strategy to investigate the association between afterhours discharge (19:00h to 07:59h) and post-ICU hospital mortality. We applied mixed-effect multi-variable linear regression to assess the relationship between discharge organ dysfunction and afterhours discharge. We then applied mixed-effect multi-variable logistic regression to evaluate the direct, indirect and integrated associations of afterhours discharge on hospital mortality and hospitalization duration.
Results: Of 10,463 patients, 23.7% (n=2,480) were discharged afterhours, of which 27.4% occurred on a holiday or weekend. This varied significantly by ICU size, type, and site. Patients discharged afterhours were more likely medical admissions, had greater multi-morbidity and illness acuity. Greater SOFA score in the 72 hours prior to discharge was not associated with afterhours discharge; however, was associated with hospital mortality (adjusted-OR 1.23; 95%CI,1.18-1.28). Afterhours discharge was associated with higher hospital mortality (adjusted-OR 1.19; 95%CI, 1.01-1.39), increased hospital stay (adjusted-OR 1.10; 95%CI,1.09-1.11) and increased post-ICU stay (adjusted-OR 1.16; 95%CI,1.14-1.17).
Conclusions: Afterhours discharge is common, occurring in 1 in 4 discharges, and is widely variable across ICUs. Patients discharged afterhours have greater risk of hospital mortality and prolonged hospitalization.
Introduction: Mortality statistics constitute a pivotal element in informing public health policymaking in critical care settings. Mortality rates exhibit temporal variability, and their quantification is susceptible to well-established biases that have been exacerbated in the backdrop of the COVID-19 pandemic. A multitude of factors contribute to the process of patients’ outcomes within the intensive care unit (ICU) setting. The primary aim of this study is to compare the mortality rate observed during the initial and subsequent phases of the COVID-19 pandemic in non-COVID-19 patient cohorts. Secondary objectives encompass evaluating the demographic and clinical factors and admission times to the ICU as an independent predictor affecting mortality.
Methods and materials: A retrospective investigation of the data gathered from 1127 non-COVID-19 patients admitted to an ICU situated in Nicosia, Cyprus between March 2020 and December 2022 was performed. We divided the study period into two distinct timeframes. The first period spanned from the onset of the COVID-19 pandemic up until January 2021, coinciding with the relaxation of COVID-related restrictions. The second period was defined as the period when restrictions were not applied. The time of admission to the ICU is categorized as either off-hours or business hours. We recorded various patient characteristics, including age, gender, Acute Physiology and Chronic Health Evaluation II (APACHE II), Glasgow Coma Scale (GCS), Sequential Organ Failure Assessment (SOFA) scores, hospitalization duration, discharge details, mortality events with precise timestamps and primary diagnosis for admission. Multivariate logistic regression analysis was performed with these characteristics to predict the likelihood of mortality.
Results: This study included 632 males (56.1%) and 495 females (43.9%). Within the patient cohort, 653 patients (57.9%) were discharged from the ICU, while 474 patients (42.1%) experienced mortality during their ICU stay. No significant correlation was found whether patients were admitted to ICU during the first or second period of the COVID-19 pandemic. There was a significant difference in the comparison of outcomes within the ICU between the off-hours and business hours (p=0.001). A total of 329 of 618 (53.2%) patients admitted in off-hours and 145 of 509 (28.4%) patients admitted in business hours died. Moreover, the mean GCS, APACHE II and SOFA scores were higher in patients admitted during off-hours. APACHE II score (OR: 1.11, 95% CI: 1.06 to 1.15, p<0.01), SOFA (OR: 1.21, 95% CI: 1.10 to 1.31, p<0.01) and GCS (OR: 0.88, 95% CI: 0.84 to 0.92, p<0.01) scores and admission to the ICU in off-hours 2.63 (1.91-3.67) were significantly associated with mortality.
Conclusion: The results of this retrospective cohort analysis have shown that the mortality rate was higher in non-COVID-19 patients admitted to ICU during off-hours compared to those admitted during business hours. However, no significant difference was found in the mortality rate between the admissions during the first and second periods of the COVID-19 pandemic.
Background:
Previous studies demonstrated a 'weekend effect' and a 'night effect' of increased mortality among patients admitted during weekends or night shifts, presumably due to understaffing. In this study, we rather examined whether death during hospitalization follows a similar effect regardless of admission time.
Methods:
A retrospective cohort study among deceased patients hospitalized in the internal medicine wing of a tertiary medical center in Israel, between 2019-2020. Demographic and medical data were retrieved from electronic medical charts. Causes of death were specifically catogrized. We applied statistical models to test for differences in mortality using incidence rate ratio (IRR) according to the day, time and cause of death.
Results:
1,278 deceased patients were included. All-cause mortality was similar among weekends and weekdays. When sepsis was the cause of death, higher IRR were demonstrated on Fridays in comparison to weekdays (IRR 1.4 95% CI 1.1-1.9, p<0.05). Other causes of death were not consistent with a 'weekend effect'. Mortality during nightshifts was higher in comparison to the afternoon (IRR 1.5 95% CI 1.3-4.7) and similar to the morning (IRR 1 95% CI 0.9-1.2).
Conclusion:
Our study did not find a pattern of 'weekend effect' or 'night effect' on all-cause mortality among hospitalized patients in internal medicine wards. Our findings suggests that perhaps specifically death from sepsis, and not all-cause mortality, can be used as a surrogate for the measurement of understaffing or quality of care in the internal ward. This article is protected by copyright. All rights reserved.
Background
There is conflicting evidence on the association between afterhours discharge from the intensive care unit (ICU) and hospital mortality. We examined the effects of afterhours discharge, including the potential effect of residual organ dysfunction, on hospital mortality in a large integrated health region.
Methods
We performed a multi-center retrospective cohort study of 10,463 adults discharged from 9 mixed medical/surgical ICUs in Alberta from June 2012 to December 2014. We applied a 2-stage modeling strategy to investigate the association between afterhours discharge (19:00h to 07:59h) and post-ICU hospital mortality. We applied mixed-effect multi-variable linear regression to assess the relationship between discharge organ dysfunction and afterhours discharge. We then applied mixed-effect multi-variable logistic regression to evaluate the direct, indirect and integrated associations of afterhours discharge on hospital mortality and hospitalization duration.
Results
Of 10,463 patients, 23.7% (n = 2,480) were discharged afterhours, of which 27.4% occurred on a holiday or weekend. This varied significantly by ICU size, type, and site. Patients discharged afterhours were more likely medical admissions, had greater multi-morbidity and illness acuity. A greater average SOFA score in the 72 hours prior to ICU discharge was not associated with afterhours discharge. However, a greater average SOFA score was associated with hospital mortality (adjusted-odds ratio [OR], 1.23; 95% CI, 1.18-1.28). Afterhours discharge was associated with higher hospital mortality (adjusted-OR, 1.19; 95% CI, 1.01-1.39), increased hospital stay (adjusted-risk ratio [RR], 1.10; 95% CI, 1.09-1.11) and increased post-ICU stay (adjusted-RR, 1.16; 95% CI, 1.14-1.17) when compared with workhours discharge.
Conclusions
Afterhours discharge is common, occurring in 1 in 4 discharges, and is widely variable across ICUs. Patients discharged afterhours have greater risk of hospital mortality and prolonged hospitalization.
