Dong, Yue

Background Adherence to evidence-based care processes and patient outcomes in intensive care units (ICUs) can be influenced by staffing and resource availability. We aimed to evaluate if there is a weekend effect on adherence to evidence-based care processes, and hospitalization outcomes and whether a checklist implementation could mitigate potential differences. Methods Post hoc analysis of the Checklist for Early Recognition and Treatment of Acute Illness and Injury (CERTAIN) study dataset collected before and after checklist implementation in 34 ICUs across 15 countries (2013-2017). Admission days were classified as ‘weekend/holidays’ or ‘weekdays’ according to local work schedules and public holidays. The primary outcome was the omission of 10 evidence-based care processes addressed in the checklist. Mortality and length of stay differences between weekend/holiday and weekday admissions were evaluated as secondary outcomes. Results 4256 patients contributed 1141 weekend versus 3501 weekday observation days pre-intervention, and 2014 versus 6507 post-intervention. Pre-intervention, peptic ulcer prophylaxis was omitted more frequently on weekends/holidays than weekdays (adjusted rate ratio [aRR], 0.58 [95%–confidence interval [CI] 0.38-0.88), whereas head-of-bed elevation was omitted more often on weekdays than on weekends/holidays (aRR, 3.17 [1.14-8.86]). Post-intervention, peptic ulcer prophylaxis omission rates became similar (aRR, 1.03 [0.68-1.56], but head-of-bed elevation became omitted more often on weekends than on weekdays (aRR, 0.63 [0.45-0.88]). Post-intervention, oral care was omitted more frequently on weekends/holidays than in weekdays (aRR, 0.63 [0.45-0.9]), and central catheter removal was more frequent on weekdays than in weekends/holidays (aRR, 1.11 [1.02-1.21]). No significant differences in mortality or length of stay were found. Conclusion A weekend effect influenced adherence to some care processes. While checklist implementation improved overall adherence, some disparities diminished, while new ones emerged. Organizational, cultural, and temporal factors should be further studied to optimize care delivery across all times and settings. Clinical Trial Registration Number NCT01973829

OBJECTIVES: The goal of this scoping review was to review some of the challenges hospitals faced in dealing with the shortage of ventilators during the COVID-19 pandemic and the solutions they were able to implement or suggested. By highlighting these problems and solutions, we hope this review can catalyze further discussions about how to better prepare for future pandemics and medical supply shortages. DATA SOURCES: A comprehensive search strategy using identifying key words was applied to several different databases to procure relevant literature. STUDY SELECTION: Four thousand two hundred fifty-nine studies were found in the initial search. Inclusion and exclusion criteria were created and applied to screen studies. Included studies focused on the supply and distribution of ventilators during the COVID-19 pandemic. In the case where reviewers disagreed about whether a study should be included, a third reviewer acted as a tie-breaker. DATA EXTRACTION: Thirty-three studies were included for final data extraction. Two independent reviewers collected various data points from these studies, including the main challenges discussed by the authors, the level of ventilator shortage being addressed, whether ventilator sharing was discussed, and the limitations of the study. DATA SYNTHESIS: A third reviewer compared the collected data and decided on the results. CONCLUSIONS: Some of the common solutions for the ventilator shortage discussed included augmenting overall ventilator supply through increased production, transporting ventilators between hospitals, ventilator sharing, designing new ventilators, and repurposing other resources to help address shortages of supplies.

ABSTRACT Understanding clinical trajectories of sepsis patients is crucial for prognostication, resource planning, and to inform digital twin models of critical illness. This study aims to identify common clinical trajectories based on dynamic assessment of cardiorespiratory support using a validated electronic health record data that covers retrospective cohort of 19,177 patients with sepsis admitted to intensive care units (ICUs) of Mayo Clinic Hospitals over 8-year period. Patient trajectories were modeled from ICU admission up to 14 days using an unsupervised machine learning two-stage clustering method based on cardiorespiratory support in ICU and hospital discharge status. Of 19,177 patients, 42% were female with a median age of 65 (interquartile range [IQR], 55–76) years, The Acute Physiology, Age, and Chronic Health Evaluation III score of 70 (IQR, 56–87), hospital length of stay (LOS) of 7 (IQR, 4–12) days, and ICU LOS of 2 (IQR, 1–4) days. Four distinct trajectories were identified: fast recovery (27% with a mortality rate of 3.5% and median hospital LOS of 3 (IQR, 2–15) days), slow recovery (62% with a mortality rate of 3.6% and hospital LOS of 8 (IQR, 6–13) days), fast decline (4% with a mortality rate of 99.7% and hospital LOS of 1 (IQR, 0–1) day), and delayed decline (7% with a mortality rate of 97.9% and hospital LOS of 5 (IQR, 3–8) days). Distinct trajectories remained robust and were distinguished by Charlson Comorbidity Index, The Acute Physiology, Age, and Chronic Health Evaluation III scores, as well as day 1 and day 3 SOFA ( P < 0.001 ANOVA). These findings provide a foundation for developing prediction models and digital twin decision support tools, improving both shared decision making and resource planning.

The Human Factors (HF) track at the Annual Healthcare Distance Simulation Summit focuses on improving the effectiveness of distance simulation utilizing human factors principles. During this presentation, we will 1. review the work to-date of the HF track of the Distance Simulation Summit, 2. discuss current opportunities for collaboration between human factors practitioners and simulationists, and 3. introduce ideas for future work. The potential target audiences for this discussion are researchers and practitioners who are interested in or involved in distance simulation or simulation in healthcare generally, educators who want to learn how to use distance simulation effectively and efficiently, and healthcare professionals and students who want to enhance their skills and knowledge about distance simulation. The presentation will stimulate discussion and feedback from the audience, which can enrich the knowledge base and generate new research questions and directions for distance simulation.