Associations between hospital occupancy, intensive care unit transfer delay and hospital mortality

Ofoma, Uchenna R.; Montoya, Juan; Saha, Debdoot; Berger, Andrea; Kirchner, H. Lester; McIlwaine, John; Kethireddy, Shravan

doi:10.1016/j.jcrc.2020.04.009

Cited by 5 publications

(5 citation statements)

References 37 publications

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“…Since the results represent the overall access to intensive care regardless of the etiology of the disease, the consequences drawn from low accessibility may differ depending on the medical focus. However, even though studies analyzing in-hospital delays from the general ward to intensive care units have shown that ICU transfer delays are associated with higher mortality, necessary to that end were delays of at least 1 or 2 h [24,25]. This being said, the average difference of 15 min travel time reported in our study may not be relevant for the majority of medical emergencies.…”

Section: Discussioncontrasting

confidence: 58%

Access to intensive care in 14 European countries: a spatial analysis of intensive care need and capacity in the light of COVID-19

et al. 2020

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Purpose: The coronavirus disease 2019 (COVID-19) poses major challenges to health-care systems worldwide. This pandemic demonstrates the importance of timely access to intensive care and, therefore, this study aims to explore the accessibility of intensive care beds in 14 European countries and its impact on the COVID-19 case fatality ratio (CFR). Methods: We examined access to intensive care beds by deriving (1) a regional ratio of intensive care beds to 100,000 population capita (accessibility index, AI) and (2) the distance to the closest intensive care unit. The crosssectional analysis was performed at a 5-by-5 km spatial resolution and results were summarized nationally for 14 European countries. The relationship between AI and CFR was analyzed at the regional level. Results: We found national-level differences in the levels of access to intensive care beds. The AI was highest in Germany (AI = 35.3), followed by Estonia (AI = 33.5) and Austria (AI = 26.4), and lowest in Sweden (AI = 5) and Denmark (AI = 6.4). The average travel distance to the closest hospital was highest in Croatia (25.3 min by car) and lowest in Luxembourg (9.1 min). Subnational results illustrate that capacity was associated with population density and national-level inventories. The correlation analysis revealed a negative correlation of ICU accessibility and COVID-19 CFR (r = − 0.57; p < 0.001). Conclusion: Geographical access to intensive care beds varies significantly across European countries and low ICU accessibility was associated with a higher proportion of COVID-19 deaths to cases (CFR). Important differences in access are due to the sizes of national resource inventories and the distribution of health-care facilities relative to the human population. Our findings provide a resource for officials planning public health responses beyond the current COVID-19 pandemic, such as identifying potential locations suitable for temporary facilities or establishing logistical plans for moving severely ill patients to facilities with available beds.

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Section: Discussioncontrasting

confidence: 58%

Access to intensive care in 14 European countries: a spatial analysis of intensive care need and capacity in the light of COVID-19

et al. 2020

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Section: Discussionmentioning

confidence: 99%

“…26 Another study in the United States showed that lack of bed availability was associated with delayed transfer of patients requiring intensive care, just as delay in obtaining an intensive care unit (ICU) bed was associated with more hospital deaths and ICU re-admissions. 27 Lack of hospital bed availability also causes user dissatisfaction, as demonstrated by a study of hospitals in England where the bed occupancy rate showed a positive association with mortality and a negative association with health improvements. 28 The availability and occupancy of hospital beds is very relevant, even more so when catastrophic or pandemic events occur.…”

Section: Discussionmentioning

confidence: 99%

Disaster Preparedness and Hospital Safety in State Hospitals in Lima (Peru)

Zegarra

Arévalo-Ipanaqué

Sánchez

et al. 2023

Prehosp. Disaster med.

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Introduction: Peru’s health infrastructures, particularly hospitals, are exposed to disaster threats of different natures. Traditionally, earthquakes have been the main disaster in terms of physical and structural vulnerability, but the coronavirus disease 2019 (COVID-19) pandemic has also shown their functional vulnerability. Public hospitals in Lima are very different in terms of year constructed, type of construction, and number of floors, making them highly vulnerable to earthquakes. In addition, they are subject to a high demand for care daily. Therefore, if a major earthquake were to occur in Lima, the hospitals would not have the capacity to respond to the high demand. Objective: The aim of this study was to analyze the Hospital Safety Index (HSI) in hospitals in Lima (Peru). Materials and Methods: This was a cross-sectional observational study of 18 state-run hospitals that met the inclusion criteria; open access data were collected for the indicators proposed by the Pan American Health Organization (PAHO) Version 1. Associations between variables were calculated using the chi-square test, considering a confidence level of 95%. A P value less than .05 was considered to determine statistical significance. Results: The average bed occupancy rate was 90%, the average age was 70 years, on average had one bed per 25,126 inhabitants, and HSI average score was 0.36 with a vulnerability of 0.63. No association was found between HSI and hospital characteristics. Conclusion: Most of the hospitals were considered Category C in earthquake and disaster safety, and only one hospital was Category A. The hospital situation needs to be clarified, and the specific deficiencies of each institution need to be identified and addressed according to their own characteristics and context.

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“…It is well documented that increases in hospital occupancy past a certain “tipping point” correlate with worsening clinical outcomes. 23 , 24 , 25 , 26 These outcomes may include reductions in quality of care, such as increases in patient mortality, nosocomial infections, adverse events, and readmission. 6 This relationship has been studied in a variety of infectious diseases, including in H1N1, where 1% increases in acute respiratory infection admissions were associated with 0.25% increases in nonacute respiratory infection mortality, 4 and in COVID-19, where increased COVID-19 admissions are associated with unnecessarily high mortality rates.…”

Section: Discussionmentioning

confidence: 99%

Patterns in the Pandemic: Disproportionate Patient Burdens Among Regional Hospitals

Corcoran

Ramsey

Franzen

et al. 2022

Annals of Emergency Medicine

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Associations between hospital occupancy, intensive care unit transfer delay and hospital mortality

Cited by 5 publications

References 37 publications

Access to intensive care in 14 European countries: a spatial analysis of intensive care need and capacity in the light of COVID-19

Access to intensive care in 14 European countries: a spatial analysis of intensive care need and capacity in the light of COVID-19

Disaster Preparedness and Hospital Safety in State Hospitals in Lima (Peru)

Patterns in the Pandemic: Disproportionate Patient Burdens Among Regional Hospitals

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