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Numbers of critical care beds corrected for size of population (per 100,000 inhabitants) for European countries  

Numbers of critical care beds corrected for size of population (per 100,000 inhabitants) for European countries  

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To quantify the numbers of critical care beds in Europe and to understand the differences in these numbers between countries when corrected for population size and gross domestic product. Prospective data collection of critical care bed numbers for each country in Europe from July 2010 to July 2011. Sources were identified in each country that coul...

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The Dutch population is ageing and it is unknown how this is affecting trends in the percentage of hospital and intensive care unit (ICU) admissions attributable to patients aged 80 years or older, the very elderly. We present data on the percentage of the very elderly in the general population and the percentage of hospital admissions attributable...

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... The overall high numbers of transfers may partly be explained by centralisation of specialised care to the few highly populated centres in our otherwise sparsely populated country. However, we believe that the large numbers of ICU-to-ICU capacity transfers also reflects the low overall number of available ICU beds in Sweden; one of the lowest in Europe [22,23]. The high rate of capacity transfers suggest that ICUs regularly deliver care close to their surge capacity and prefer to transfer already admitted patients instead of refusing new patients with urgent needs. ...
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Background Transfers from one intensive care unit (ICU) to another ICU are associated with increased length of intensive care and hospital stay. Inter-hospital ICU transfers are carried out for three main reasons: clinical transfers, capacity transfers and repatriations. The aim of the study was to show that different ICU transfers differ in risk-adjusted mortality rate with repatriations having the least risk. Results Observational cohort study of adult patients transferred between Swedish ICUs during 3 years (2016–2018) with follow-up ending September 2019. Primary and secondary end-points were survival to 30 days and 180 days after discharge from the first ICU. Data from 75 ICUs in the Swedish Intensive Care Register, a nationwide intensive care register, were used for analysis (89% of all Swedish ICUs), covering local community hospitals, district general hospitals and tertiary care hospitals. We included adult patients (16 years or older) admitted to ICU and subsequently discharged by transfer to another ICU. Only the first admission was used. Exposure was discharge to any other ICU (ICU-to-ICU transfer), whether in the same or in another hospital. Transfers were grouped into three predefined categories: clinical transfer, capacity transfer, and repatriation. We identified 15,588 transfers among 112,860 admissions (14.8%) and analysed 11,176 after excluding 4112 repeat transfer of the same individual and 300 with missing risk adjustment. The majority were clinical transfers (62.7%), followed by repatriations (21.5%) and capacity transfers (15.8%). Unadjusted 30-day mortality was 25.0% among capacity transfers compared to 14.5% and 16.2% for clinical transfers and repatriations, respectively. Adjusted odds ratio (OR) for 30-day mortality were 1.25 (95% CI 1.06–1.49 p = 0.01) for capacity transfers and 1.17 (95% CI 1.02–1.36 p = 0.03) for clinical transfers using repatriation as reference. The differences remained 180 days post-discharge. Conclusions There was a large proportion of ICU-to-ICU transfers and an increased odds of dying for those transferred due to other reasons than repatriation.
... Although the number of beds is rapidly increasing in response to the COVID-19 pandemic, the Japanese Society of Intensive Care Medicine reported that there were 7015 ICU beds and 13,003 HDU beds nationwide in 2020, with an overall intensive care bed count of approximately 15.9 beds per 100,000 population [20]. In contrast, the number of intensive care beds per 100,000 population in the United States and Germany was 34.7 (as of 2009) and 29.2 (as of 2010), respectively [21,22]. Moreover, Japan has only 2115 certified intensivists (as of April 1, 2021) compared with approximately 12,000 certified intensivists in the United States. ...
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Background Septic shock is a common and life-threatening condition that requires intensive care. Intensive care units (ICUs) in Japan are classified into ICUs and high-dependency care units (HDUs), depending on presence of full-time certified intensivists and the number of assigned nurses. Compared with other developed countries, there are fewer intensive care beds and certified intensivists in Japan; therefore, non-intensivists often treat patients with septic shock in HDUs. It is unknown where we should treat patients with septic shock because no studies have compared the clinical outcomes between ICU and HDU treatment. This study aimed to elucidate which units should admit patients with septic shock by comparing mortality data and resource use between ICU and HDU admissions. Methods In this retrospective cohort study, we used a nationwide Japanese administrative database to identify adult patients with septic shock who were admitted to ICUs or HDUs between January 2010 and February 2021. The patients were divided into two groups, based on admittance to ICU or HDU on the day of hospitalization. The primary outcome was 30-day all-cause mortality adjusted for covariates using Cox regression analyses; the secondary outcomes were the length of ICU or HDU stay and length of hospital stay. Results Of the 10,818 eligible hospitalizations for septic shock, 6584 were in the ICU group, and 4234 were in the HDU group. Cox regression analyses revealed that patients admitted to the ICUs had lower 30-day mortality (adjusted hazard ratio: 0.89; 95% confidence interval: 0.83–0.96; P = 0.005). Linear regression analyses showed no significant difference in hospital length of stay or ICU or HDU length of stay. Conclusions An association was observed between ICU admission and lower 30-day mortality in patients with septic shock. These findings could provide essential insights for building a more appropriate treatment system.
... An ageing society could also induce an increase in ICU admissions and ICU demand. Studies have shown that the organization, structure, and delivery of critical care in China are different from those in Asia, Europe and North America [13][14][15][16]. Critical care medicine in mainland China is still in a phase of development. ...
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Background: Hospital and ICU structural factors are key factors affecting the quality of care as well as ICU patient outcomes. However, the data from China are scarce. This study was designed to investigate how differences in patient outcomes are associated with differences in hospital and ICU structure variables in China throughout 2019. Methods: This was a multicenter observational study. Data from a total of 2820 hospitals were collected using the National Clinical Improvement System Data that reports ICU information in China. Data collection consisted of a) information on the hospital and ICU structural factors, including the hospital type, number of beds, staffing, among others, and b) ICU patient outcomes, including the mortality rate as well as the incidence of ventilator-associated pneumonia (VAP), catheter-related bloodstream infections (CRBSIs), and catheter-associated urinary tract infections (CAUTIs). Generalized linear mixed models were used to analyse the association between hospital and ICU structural factors and patient outcomes. Results: The median ICU patient mortality was 8.02% (3.78%, 14.35%), and the incidences of VAP, CRBSI, and CAUTI were 5.58 (1.55, 11.67) per 1000 ventilator days, 0.63 (0, 2.01) per 1000 catheter days, and 1.42 (0.37, 3.40) per 1000 catheter days, respectively. Mortality was significantly lower in public hospitals (β = - 0.018 (- 0.031, - 0.005), p = 0.006), hospitals with an ICU-to-hospital bed percentage of more than 2% (β = - 0.027 (- 0.034, -0.019), p < 0.001) and higher in hospitals with a bed-to-nurse ratio of more than 0.5:1 (β = 0.009 (0.001, 0.017), p = 0.027). The incidence of VAP was lower in public hospitals (β = - 0.036 (- 0.054, - 0.018), p < 0.001). The incidence of CRBSIs was lower in public hospitals (β = - 0.008 (- 0.014, - 0.002), p = 0.011) and higher in secondary hospitals (β = 0.005 (0.001, 0.009), p = 0.010), while the incidence of CAUTIs was higher in secondary hospitals (β = 0.010 (0.002, 0.018), p = 0.015). Conclusion: This study highlights the association between specific ICU structural factors and patient outcomes. Modifying structural factors is a potential opportunity that could improve patient outcomes in ICUs.
... Of note, the Netherlands healthcare system has less ICU beds per capita than other European countries, i.e. 6.4 per 100,000. For instance, Belgium with 15.9 or Germany with 29.2 have significantly more ICU beds per 100,000 inhabitants [2]. This combined with both the high number of patients and their longer length of stay (when compared to average ICU patients) caused a limitation in the numbers of available ICU beds. ...
... In our cohort we feel that a more liberal attitude towards admission of patients with comorbidities was the case in Wave 2. The decline in comorbidities in Wave 3 may be associated with the decrease in age due to the vaccination program. Moreover, the differences between countries could also be explained by the number of available ICU beds per country [2]. ...
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Background To assess trends in the quality of care for COVID-19 patients at the ICU over the course of time in the Netherlands. Methods Data from the National Intensive Care Evaluation (NICE)-registry of all COVID-19 patients admitted to an ICU in the Netherlands were used. Patient characteristics and indicators of quality of care during the first two upsurges (N = 4215: October 5, 2020–January 31, 2021) and the final upsurge of the second wave, called the ‘third wave’ (N = 4602: February 1, 2021–June 30, 2021) were compared with those during the first wave (N = 2733, February–May 24, 2020). Results During the second and third wave, there were less patients treated with mechanical ventilation (58.1 and 58.2%) and vasoactive drugs (48.0 and 44.7%) compared to the first wave (79.1% and 67.2%, respectively). The occupancy rates as fraction of occupancy in 2019 (1.68 and 1.55 vs. 1.83), the numbers of ICU relocations (23.8 and 27.6 vs. 32.3%) and the mean length of stay at the ICU (HRs of ICU discharge = 1.26 and 1.42) were lower during the second and third wave. No difference in adjusted hospital mortality between the second wave and the first wave was found, whereas the mortality during the third wave was considerably lower (OR = 0.80, 95% CI [0.71–0.90]). Conclusions These data show favorable shifts in the treatment of COVID-19 patients at the ICU over time. The adjusted mortality decreased in the third wave. The high ICU occupancy rate early in the pandemic does probably not explain the high mortality associated with COVID-19.
... In European reports published well before and during the pandemic, there were similar numbers of critical care beds per 100 000 population between Denmark, the UK and Greece (approx. 6 per 100 000) [20,21]. Thus, perhaps it is more about a culture for rationale allocation of hospital resources to those who are at highest risk rather than their general availability in the health care system [22]. ...
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Background Emergency laparotomy (EL) is accompanied by high post-operative morbidity and mortality which varies significantly between countries and populations. The aim of this study is to report outcomes of emergency laparotomy in Greece and to compare them with the results of the National Emergency Laparotomy Audit (NELA). Methods This is a multicentre prospective cohort study undertaken between 01.2019 and 05.2020 including consecutive patients subjected to EL in 11 Greek hospitals. EL was defined according to NELA criteria. Demographics, clinical variables, and post-operative outcomes were prospectively registered in an online database. Multivariable logistic regression analysis was used to identify independent predictors of post-operative mortality. Results There were 633 patients, 53.9% males, ASA class III/IV 43.6%, older than 65 years 58.6%. The most common operations were small bowel resection (20.5%), peptic ulcer repair (12.0%), adhesiolysis (11.8%) and Hartmann’s procedure (11.5%). 30-day post-operative mortality reached 16.3% and serious complications occurred in 10.9%. Factors associated with post-operative mortality were increasing age and ASA class, dependent functional status, ascites, severe sepsis, septic shock, and diabetes. HELAS cohort showed similarities with NELA patients in terms of demographics and preoperative risk. Post-operative utilisation of ICU was significantly lower in the Greek cohort (25.8% vs 56.8%) whereas 30-day post-operative mortality was significantly higher (16.3% vs 8.7%). Conclusion In this study, Greek patients experienced markedly worse mortality after emergency laparotomy compared with their British counterparts. This can be at least partly explained by underutilisation of critical care by surgical patients who are at high risk for death.
... Although speculative, one contributing factor might be a difference in pre-hospital and in-hospital triage systems between the two countries. For example, the number of ICU beds in the UK (6.6 ICU beds/100 000 people) 27 is considerably lower than in the US (28 ICU beds/100 000 people), 28 so it seems conceivable that the threshold to admit patients with a poor prognosis to the ICU (and maintain ICU support) is higher in the UK than in the USA, which might decrease the overall frequency of coma in the UK. Coincidence or not, the ratio of comatose UK and US family members on the day of the survey was very similar to the ratio of ICU beds in the two countries (1-5 versus 1-4.3). ...
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The epidemiology of coma is unknown because case ascertainment with traditional methods is difficult. Here, we used crowdsourcing methodology to estimate the incidence and prevalence of coma in the UK and the USA. We recruited UK and US laypeople (aged ≥18 years) who were nationally representative (i.e. matched for age, gender and ethnicity according to census data) of the UK and the USA, respectively, utilizing a crowdsourcing platform. We provided a description of coma and asked survey participants if they—‘right now’ or ‘within the last year’—had a family member in coma. These participants (UK n = 994, USA n = 977) provided data on 30 387 family members (UK n = 14 124, USA n = 16 263). We found more coma cases in the USA (n = 47) than in the UK (n = 20; P = 0.009). We identified one coma case in the UK (0.007%, 95% confidence interval 0.00–0.04%) on the day of the survey and 19 new coma cases (0.13%, 95% confidence interval 0.08–0.21%) within the preceding year, resulting in an annual incidence of 135/100 000 (95% confidence interval 81–210) and a point prevalence of 7 cases per 100 000 population (95% confidence interval 0.18–39.44) in the UK. We identified five cases in the USA (0.031%, 95% confidence interval 0.01–0.07%) on the day of the survey and 42 new cases (0.26%, 95% confidence interval 0.19–0.35%) within the preceding year, resulting in an annual incidence of 258/100 000 (95% confidence interval 186–349) and a point prevalence of 31 cases per 100 000 population (95% confidence interval 9.98–71.73) in the USA. The five most common causes were stroke, medically induced coma, COVID-19, traumatic brain injury and cardiac arrest. To summarize, for the first time, we report incidence and prevalence estimates for coma across diagnosis types and settings in the UK and the USA using crowdsourcing methods. Coma may be more prevalent in the USA than in the UK, which requires further investigation. These data are urgently needed to expand the public health perspective on coma and disorders of consciousness.
... 4,19e21 Rapid demographic and societal changes have led to an escalating burden of noncommunicable diseases. Supply of healthcare varies broadly worldwide, 22,23 including within Latin America, with a mixture of social, private, and government-funded systems. Latin America describes a geographic area, including 25 nations, with countries presenting some of the highest income disparities worldwide. ...
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Background: Reported data suggest that 4.2 million deaths will occur within 30 days of surgery worldwide each year, half of which are in low-and middle-income countries. Postoperative complications are a leading cause of long-term morbidity and mortality. Patients who survive and leave the hospital after surgical complications regularly experience reductions in long-term survival and functional independence, resulting in increased costs. With a high volume of surgery performed, there is a growing perception of the substantial impact of even minor enhancements in perioperative care. The Latin American Surgical Outcomes Study (LASOS) is an international, multicentre, prospective cohort study of adults submitted to in-patient surgery in Latin America aiming to provide detailed data describing postoperative complications and surgical mortality. Methods: LASOS is a 7 day cohort study of adults undergoing surgery in Latin America. Details of preoperative risk factors, intraoperative care, and postoperative outcomes will be collected. The primary outcome will be in-hospital postoperative complications of any cause. Secondary outcomes include in-hospital all-cause mortality, duration of hospital stay after surgery, and admission to a critical care unit within 30 days after surgery during the index hospitalisation. Results: The LASOS results will be published in peer-reviewed journals, reported and presented at international meetings , and widely disseminated to patients and public in participating countries via mainstream and social media. Conclusions: The LASOS may augment our understanding of postoperative complications and surgial mortality in Latin America. Clinical trial registration: NCT05169164.
... In Belgium, there are no criteria for ICU discharge and the decision is often taken by the medical team alone. This result was certainly also influenced by the rather high occupancy rate in the study despite the high number of ICU beds in Belgium (Chrusch et al., 2009;Fergusson et al., 2020;Rhodes et al., 2012). In addition, patients who died quickly could also have influenced this result. ...
Introduction: Hospitals with better nursing resources report more favourable patient outcomes with almost no difference in cost as compared to those with worse nursing resources. The aim of this study was to assess the association between nursing cost per intensive care unit bed and patient outcomes (mortality, readmission, and length of stay). Methodology: This was a retrospective cohort study using data collected from the intensive care units of 17 Belgian hospitals from January 01 to December 31, 2018. Hospitals were dichotomized using median annual nursing cost per bed. A total of 18,235 intensive care unit stays were included in the study with 5,664 stays in the low-cost nursing group and 12,571 in the high-cost nursing group. Results: The rate of high length of stay outliers in the intensive care unit was significantly lower in the high-cost nursing group (9.2% vs 14.4%) compared to the low-cost nursing group. Intensive care unit readmission was not significantly different in the two groups. Mortality was lower in the high-cost nursing group for intensive care unit (9.9% vs 11.3%) and hospital (13.1% vs 14.6%) mortality. The nursing cost per intensive care bed was different in the two groups, with a median [IQR] cost of 159,387€ [140,307–166,690] for the low-cost nursing group and 214,032€ [198,094–230,058] for the high-cost group. In multivariate analysis, intensive care unit mortality (OR = 0.80, 95% CI: 0.69–0.92, p < 0.0001), in-hospital mortality (OR = 0.82, 95% CI: 0.72–0.93, p < 0.0001), and high length of stay outliers (OR = 0.48, 95% CI: 0.42–0.55, p < 0.0001) were lower in the high-cost nursing group. However, there was no significant effect on intensive care readmission between the two groups (OR = 1.24, 95% CI: 0.97–1.51, p > 0.05). Conclusions: This study found that higher-cost nursing per bed was associated with significantly lower intensive care unit and in-hospital mortality rates, as well as fewer high length of stay outliers, but had no significant effect on readmission to the intensive care unit.
... Obwohl es in Deutschland, verglichen mit allen anderen europäischen Ländern, überdurchschnittlich viele Intensiv-und Intermediate-Care-Betten bezogen auf die Einwohnerzahl gibt (etwa 30 Betten pro 100.000 Einwohner; [6]), kommt es paradoxerweise in diesem Bereich immer wieder zu Engpässen in der Patientenversorgung. Diese Engpässe sind maßgeblich darauf zurückzuführen, dass sowohl die Anzahl der Intensivbetten als auch die Behandlungsfälle in Deutschland kontinuierlich gestiegen sind, während im selben Zeitraum die Anzahl an Pflegekräften und Fachpflegekräften abgenommen hat [7]. Eine geringe Personalstärke und ein geringer Qualifikationsmix erhöhen die Wahrscheinlichkeit, dass Patienten im Krankenhaus sterben [8]. ...
... However, the panelists represented with their expertise and input mainly very developed countries, where a high standard of intensive care is provided, although the availability of ICU beds per 100.000 capita of population varies widely [33]. The definition of a rather high consensus level with ≥ 90% for criteria inclusion and 5 rounds of partially reiterations of voting enabled consistency checks and fine-tuning of the proposed criteria. ...
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Background/purpose Discharge decisions in Intensive Care Unit (ICU) patients are frequently taken under pressure to free up ICU beds. In the absence of established guidelines, the evaluation of discharge readiness commonly underlies subjective judgements. The challenge is to come to the right decision at the right time for the right patient. A premature care transition puts patients at risk of readmission to the ICU. Delayed discharge is a waste of resources and may result in over-treatment and suboptimal patient flow. More objective decision support is required to assess the individual patient’s discharge readiness but also the current care capabilities of the receiving unit. Methods In a modified online Delphi process, an international panel of 27 intensive care experts reached consensus on a set of 28 intensive care discharge criteria. An initial evidence-based proposal was developed further through the panelists’ edits, adding, comments and voting over a course of 5 rounds. Consensus was defined as achieved when ≥ 90% of the experts voted for a given option on the Likert scale or in a multiple-choice survey. Round 1 to 3 focused on inclusion and exclusion of the criteria based on the consensus threshold, where round 3 was a reiteration to establish stability. Round 4 and 5 focused on the exact phrasing, values, decision makers and evaluation time frames per criterion. Results Consensus was reached on a standard set of 28 ICU discharge criteria for adult ICU patients, that reflect the patient’s organ systems ((respiratory (7), cardiovascular (9), central nervous (1), and urogenital system (2)), pain (1), fluid loss and drainages (1), medication and nutrition (1), patient diagnosis, prognosis and preferences (2) and institution-specific criteria (4). All criteria have been specified in a binary decision metric (fit for ICU discharge vs. needs further intensive therapy/monitoring), with consented value calculation methods where applicable and a criterion importance rank with “mandatory to be met” flags and applicable exceptions. Conclusion For a timely identification of stable intensive care patients and safe and efficient care transitions, a standardized discharge readiness evaluation should be based on patient factors as well as organizational boundary conditions and involve multiple stakeholders.