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1.
Journal of Pediatric Intensive Care ; 2023.
Article in English | Web of Science | ID: covidwho-20235728

ABSTRACT

Health care throughput is the progression of patients from admission to discharge, limited by bed occupancy and hospital capacity. This study examines heart center throughput, cascading effects of limited beds, transfer delays, and nursing staffing on outcomes utilizing elective surgery cancellation during the initial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic wave. This study was a retrospective single-center study of staffing, adverse events, and transfers. The study period was January 1, 2018 to December 31, 2020 with the SARS-CoV-2 period March to May 2020. There were 2,589 patients, median age 5 months (6 days-4 years), 1,543 (60%) surgical and 1,046 (40%) medical. Mortality was 3.9% ( n = 101), median stay 5 days (3-11 days), median 1:1 nurse staffing 40% (33-48%), median occupancy 54% (43-65%) for step-down unit, and 81% (74-85%) for cardiac intensive care unit. Every 10% increase in step-down unit occupancy had a 0.5-day increase in cardiac intensive care unit stay ( p = 0.044), 2.1% increase in 2-day readmission ( p = 0.023), and 2.6% mortality increase ( p < 0.001). Every 10% increase in cardiac intensive care unit occupancy had 3.4% increase in surgical delay ( p = 0.016), 6.5% increase in transfer delay ( p = 0.020), and a 15% increase in total reported adverse events ( p < 0.01). Elective surgery cancellation is associated with reduced high occupancy days (23-10%, p < 0.001), increased 1:1 nursing (34-55%, p < 0.001), decreased transfer delays (19-4%, p = 0.008), and decreased mortality (3.7-1.5%, p = 0.044). In conclusion, Elective surgery cancellation was associated with increased 1:1 nursing and decreased mortality. Increased cardiac step-down unit occupancy was associated with longer cardiac intensive care unit stay, increased transfer, and surgical delays.

2.
Critical Care Medicine ; 51(1 Supplement):352, 2023.
Article in English | EMBASE | ID: covidwho-2190592

ABSTRACT

INTRODUCTION: Healthcare throughput is the progression of patients from admission to discharge, limited by bed occupancy and hospital capacity. This study examines Heart Center throughput, cascading effects of limited beds, transfer delays, and nursing assignments on outcomes utilizing elective surgery cancellation during the initial COVID-19 pandemic wave. METHOD(S): Nursing assignments, patient data, and transfers were collected. Elective surgery cancellation was March-May 2020. Heart Center occupancy (Stepdown Unit and Cardiac Intensive Care Unit), transfer delays, and patient outcomes were analyzed controlling for patient factors, surgical risk, staffing, and time effects. Setting(s): Retrospective single-center study Patients: Heart Center admissions January 1, 2018 - December 31, 2020. RESULT(S): There were 2,589 patients, median age 5 months (6 days-4 years), 1,543 (60%) surgical, 1,046 (40%) medical. Mortality was 3.9% (n=101), median stay 5 days (3- 11 days), median 1:1 nursing assignments 40% (33%-48%), median occupancy 54% (43%-65%) for Stepdown Unit and 81% (74%-85%) for Cardiac Intensive Care Unit. Every 10% increase in Stepdown Unit occupancy had a 0.5-day increase in Cardiac Intensive Care Unit stay (p=0.044), 2.1% increase 2-day readmission (p=0.023), and 2.6% mortality increase (p< 0.001). Every 10% increase in Cardiac Intensive Care Unit occupancy had 3.4% increase in surgical delay (p=0.016) and 6.5% increase in transfer delay (p=0.020). Elective surgery cancellation reduced high occupancy days (23% to 10%, p< 0.001), increased 1:1 nursing (34% to 55%, p< 0.001), decreased transfer delays (19% to 4%, p=0.008), and decreased mortality (3.7% to 1.5%, p=0.044). CONCLUSION(S): Cancelation of elective surgery was associated with increased 1:1 nursing assignments and decreased mortality. Increased Cardiac Stepdown Unit occupancy resulted in longer Cardiac Intensive Care Unit stay, and increased Cardiac Intensive Care Unit occupancy increased transfer and surgical delays. Additional studies are need to understand the interaction of staffing and outcomes.

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