Measuring the Impact of ICU Strain on Mortality, After-Hours Discharge, Discharge Delay, Interhospital Transfer, and Readmission in Australia With the Activity Index.

OBJECTIVES: ICU resource strain leads to adverse patient outcomes. Simple, well-validated measures of ICU strain are lacking. Our objective was to assess whether the "Activity index," an indicator developed during the COVID-19 pandemic, was a valid measure of ICU strain. DESIGN: Retrospective national registry-based cohort study. SETTING: One hundred seventy-five public and private hospitals in Australia (June 2020 through March 2022). SUBJECTS: Two hundred seventy-seven thousand seven hundred thirty-seven adult ICU patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Data from the Australian and New Zealand Intensive Care Society Adult Patient Database were matched to the Critical Health Resources Information System. The mean daily Activity index of each ICU (census total of "patients with 1:1 nursing" + "invasive ventilation" + "renal replacement" + "extracorporeal membrane oxygenation" + "active COVID-19," divided by total staffed ICU beds) during the patient's stay in the ICU was calculated. Patients were categorized as being in the ICU during very quiet (Activity index < 0.1), quiet (0.1 to < 0.6), intermediate (0.6 to < 1.1), busy (1.1 to < 1.6), or very busy time-periods (≥ 1.6). The primary outcome was in-hospital mortality. Secondary outcomes included after-hours discharge from the ICU, readmission to the ICU, interhospital transfer to another ICU, and delay in discharge from the ICU. Median Activity index was 0.87 (interquartile range, 0.40-1.24). Nineteen thousand one hundred seventy-seven patients died (6.9%). In-hospital mortality ranged from 2.4% during very quiet to 10.9% during very busy time-periods. After adjusting for confounders, being in an ICU during time-periods with higher Activity indices, was associated with an increased risk of in-hospital mortality (odds ratio [OR], 1.49; 99% CI, 1.38-1.60), after-hours discharge (OR, 1.27; 99% CI, 1.21-1.34), readmission (OR, 1.18; 99% CI, 1.09-1.28), interhospital transfer (OR, 1.92; 99% CI, 1.72-2.15), and less delay in ICU discharge (OR, 0.58; 99% CI, 0.55-0.62): findings consistent with ICU strain. CONCLUSIONS: The Activity index is a simple and valid measure that identifies ICUs in which increasing strain leads to progressively worse patient outcomes.

Nursing workforce deployment and intensive care unit strain during the COVID-19 pandemic in Victoria, Australia.

BACKGROUND: The COVID-19 pandemic demanded intensive care units (ICUs) globally to expand to meet increasing patient numbers requiring critical care. Critical care nurses were a finite resource in this challenge to meet growing patient numbers, necessitating redeployment of nursing staff to work in ICUs. OBJECTIVE: Our aim was to describe the extent and manner by which the increased demand for ICU care during the COVID-19 pandemic was met by ICU nursing workforce expansion in the late 2021 and early 2022 in Victoria, Australia. METHODS: This is a retrospective cohort study of Victorian ICUs who contributed nursing data to the Critical Health Information System from 1 December 2021 to 11 April 2022. Bedside nursing workforce data, in categories as defined by Safer Care Victoria's pandemic response guidelines, were analysed. The primary outcome was 'insufficient ICU skill mix'-whenever a site had more patients needing 1:1 critical care nursing care than the mean daily number of experienced critical care nursing staff. RESULTS: Overall, data from 24 of the 47 Victorian ICUs were eligible for analysis. Insufficient ICU skill mix occurred on 10.3% (280/2725) days at 66.7% (16/24) of ICUs, most commonly during the peak phase from December to mid-February. The insufficient ICU skill mix was more likely to occur when there were more additional ICU beds open over the 'business-as-usual' number. Counterfactual analysis suggested that had there been no redeployment of staff to the ICU, reduced nursing ratios, with inability to provide 1:1 care, would have occurred on 15.2% (415/2725) days at 91.7% (22/24) ICUs. CONCLUSION: The redeployment of nurses into the ICU was necessary. However, despite this, at times, some ICUs had insufficient staff to cope with the number and acuity of patients. Further research is needed to examine the impact of ICU nursing models of care on patient outcomes and on nurse outcomes.

The impact of nursing workforce skill-mix on patient outcomes in intensive care units in Victoria, Australia.

Objective: This article aims to examine the impact of nursing workforce skill-mix (percentage of critical care registered nurses [CCRN]) in the intensive care unit (ICU) during a patient's stay. Design: Registry linked cohort study of the Australian and New Zealand Intensive Care Society Adult Patient Database and the Critical Health Resources Information System using real-time nursing workforce data. Settings: Fifteen public and 5 private hospital ICUs in Victoria, Australia. Participants: There were 16,618 adult patients admitted between 1 December 2021 and 30 September 2022. Main outcome measures: Primary outcome: in-hospital mortality. Secondary outcomes: in-ICU mortality, development of delirium, pressure injury, duration of stay in-ICU and hospital, after-hours discharge from ICU and readmission to ICU. Results: In total, 6563 (39.5%) patients were cared for in ICUs with >75% CCRN, 7695 (46.3%) in ICUs with 50-75% CCRN, and 2360 (14.2%) in ICUs with <50% CCRN. In-hospital mortality was 534 (8.1%) vs. 859 (11.2%) vs. 252 (10.7%) respectively. After adjusting for confounders, patients cared for in ICUs with 50-75% CCRN (adjusted OR 1.21 [95% CI 1.02-1.45]) were more likely to die compared to patients in ICUs with >75% CCRN. A similar but non-significant trend was seen in ICUs with <50% CCRN (adjusted OR 1.21 [95% CI 0.94-1.55]), when compared to patients in ICUs with >75% CCRN. In-ICU mortality, delirium, pressure injuries, after-hours discharge and ICU length of stay were lower in ICUs with CCRN>75%. Conclusion: The nursing skill-mix in ICU impacts outcomes and should be routinely monitored. Health system regulators, hospital administrators and ICU leaders should ensure nursing workforce planning and education align with these findings to maximise patient outcomes.

Assessment of a novel marker of ICU strain, the ICU Activity Index, during the COVID-19 pandemic in Victoria, Australia.

Objectives: To validate a real-time Intensive Care Unit (ICU) Activity Index as a marker of ICU strain from daily data available from the Critical Health Resource Information System (CHRIS), and to investigate the association between this Index and the need to transfer critically ill patients during the coronavirus disease 2019 (COVID-19) pandemic in Victoria, Australia. Design: Retrospective observational cohort study. Setting: All 45 hospitals with an ICU in Victoria, Australia. Participants: Patients in all Victorian ICUs and all critically ill patients transferred between Victorian hospitals from 27 June to 6 September 2020. Main outcome measure: Acute interhospital transfer of one or more critically ill patients per day from one site to an ICU in another hospital. Results: 150 patients were transported over 61 days from 29 hospitals (64%). ICU Activity Index scores were higher on days when critical care transfers occurred (median, 1.0 [IQR, 0.4-1.7] v 0.6 [IQR, 0.3-1.2]; P < 0.001). Transfers were more common on days of higher ICU occupancy, higher numbers of ventilated or COVID-19 patients, and when more critical care staff were unavailable. The highest ICU Activity Index scores were observed at hospitals in north-western Melbourne, where the COVID-19 disease burden was greatest. After adjusting for confounding factors, including occupancy and lack of available ICU staff, a rising ICU Activity Index score was associated with an increased risk of a critical care transfer (odds ratio, 4.10; 95% CI, 2.34-7.18; P < 0.001). Conclusions: The ICU Activity Index appeared to be a valid marker of ICU strain during the COVID-19 pandemic. It may be useful as a real-time clinical indicator of ICU activity and predict the need for redistribution of critical ill patients.