Number Of Critical Care Beds Research Articles

Critical care bed capacity in Asian countries and regions before and during the COVID-19 pandemic: an observational study

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic highlighted the importance of critical care. The aim of the current study was to compare the number of adult critical care beds in relation to population size in Asian countries and regions before (2017) and during (2022) the pandemic. MethodsThis observational study collected data closest to 2022 on critical care beds (intensive care units and intermediate care units) in 12 middle-income and 7 high-income economies (using the 2022-2023 World Bank classification), through a mix of methods including government sources, national critical care societies, personal contacts, and data extrapolation. Data were compared with a prior study from 2017 of the same countries and regions. FindingsThe cumulative number of critical care beds per 100,000 population increased from 3.0 in 2017 to 9.4 in 2022 (p = 0.003). The median figure for middle-income economies increased from 2.6 (interquartile range [IQR] 1.7 to 7.8) to 6.6 (IQR 2.2 to 13.3), and that for high-income economies increased from 11.4 (IQR 7.3 to 22.8) to 13.9 (IQR 10.7 to 21.7). Only 3 countries did not see a rise in bed capacity. Where data were available in 2022, 10.9% of critical care beds were in single rooms (median 5.0% in middle-income and 20.3% in high-income economies), and 5.3% had negative pressure (median 0.7% in middle-income and 18.5% in high-income economies). InterpretationCritical care bed capacity in the studied Asian countries and regions increased close to three-fold from 2017 to 2022. Much of this increase was attributed to middle-income economies, but substantial heterogeneity exists.

Critical care bed capacity of Bangladesh: A Pre and Post COVID-19 pandemic survey

Background: Intensive care unit (ICU) is the backbone of critical care service delivery in a hospital. Bangladesh has been lagging behind in critical care service delivery since first ICU was established in 1978. In 2017-19 an international study reported that Bangladesh had 0.7 Critical care (ICU and HDU) bed per one lac population. This was quite low compared to South Asian countries. Growth of critical care beds across our country has been reported to be heterogeneous. The aim of this survey is to determine current strength and growth of critical care beds before the beginning of recent COVID pandemic and also at the height of pandemic when additional COVID ICUs and HDUs were introduced. Method: Data on number of ICUs and HDUs and their bed strength were obtained from different web sites of Govt. of Bangladesh as well through personal communication. Number of critical care beds were calculated at national and district level as number per one lac population. Ratio of critical care beds expressed in percentage with number of hospital beds in the hospital were calculated at national level. Data were also obtained on COVID ICU and HDU beds which were introduced temporarily from websites of ministry of Health, Govt. of Bangladesh. Results: As of now we documented (pre COVID pandemic) 2139 ICU beds (965 in Govt. hospitals) and 717 HDU beds (315 in Govt. hospitals) among 208 hospitals (Govt. hospitals 79+ Private hospitals 129) during our survey. Number of critical care beds per one lac population across the country is found to be 1.70. In hospitals with critical care beds the average ratio of critical care beds (ICU+HDU) beds compared to hospital beds is 4.34% across the country. Thirty eight of total 64 districts have no critical care facility (non COVID/pre COVID) in their local hospitals. During peak of pandemic Govt. of Bangladesh introduced and approved 1186 COVID ICU beds, 695 COVID HDU beds both at Govt. and private level on temporary basis in different hospitals including in some critical care deprived hospitals. Conclusion: Our survey concludes that growth and distribution of critical care beds (ICUS + HDUs) across Bangladesh is still heterogeneous and very much inadequate compared to the critical care need of the population. There was a temporary surge of new ICUs and HDUs to serve COVID patients at the height of COVID pandemic across the country. Health care planners of the country need to plan for developing adequate critical care man power as well as establish newer critical care facilities among existing hospitals who lack them. Bangladesh Crit Care J September 2022; 10(2): 88-98

Critical Care Requirements Under Uncontrolled Transmission of SARS-CoV-2.

Objectives. To estimate the critical care bed capacity that would be required to admit all critical COVID-19 cases in a setting of unchecked SARS-CoV-2 transmission, both with and without elderly-specific protection measures.Methods. Using electronic health records of all 2432 COVID-19 patients hospitalized in a large hospital in Madrid, Spain, between February 28 and April 23, 2020, we estimated the number of critical care beds needed to admit all critical care patients. To mimic a hypothetical intervention that halves SARS-CoV-2 infections among the elderly, we randomly excluded 50% of patients aged 65 years and older.Results. Critical care requirements peaked at 49 beds per 100 000 on April 1-2 weeks after the start of a national lockdown. After randomly excluding 50% of elderly patients, the estimated peak was 39 beds per 100 000.Conclusions. Under unchecked SARS-CoV-2 transmission, peak critical care requirements in Madrid were at least fivefold higher than prepandemic capacity. Under a hypothetical intervention that halves infections among the elderly, critical care peak requirements would have exceeded the prepandemic capacity of most high-income countries.Public Health Implications. Pandemic control strategies that rely exclusively on protecting the elderly are likely to overwhelm health care systems.

COVID-19: a simple statistical model for predicting intensive care unit load in exponential phases of the disease

One major bottleneck in the ongoing COVID-19 pandemic is the limited number of critical care beds. Due to the dynamic development of infections and the time lag between when patients are infected and when a proportion of them enters an intensive care unit (ICU), the need for future intensive care can easily be underestimated. To infer future ICU load from reported infections, we suggest a simple statistical model that (1) accounts for time lags and (2) allows for making predictions depending on different future growth of infections. We have evaluated our model for three heavily affected regions in Europe, namely Berlin (Germany), Lombardy (Italy), and Madrid (Spain). Before extensive containment measures made an impact, we first estimate the region-specific model parameters, namely ICU rate, time lag between infection, and ICU admission as well as length of stay in ICU. Whereas for Berlin, an ICU rate of 6%, a time lag of 6 days, and a stay of 12 days in ICU provide the best fit of the data, for Lombardy and Madrid the ICU rate was higher (18% and 15%) and the time lag (0 and 3 days) and the stay in ICU (3 and 8 days) shorter. The region-specific models are then used to predict future ICU load assuming either a continued exponential phase with varying growth rates (0–15%) or linear growth. By keeping the growth rates flexible, this model allows for taking into account the potential effect of diverse containment measures. Thus, the model can help to predict a potential exceedance of ICU capacity depending on future growth. A sensitivity analysis for an extended time period shows that the proposed model is particularly useful for exponential phases of the disease.

The number of critical care beds and insurance charges of mechanical ventilation in Japan

The number of critical care beds and insurance charges of mechanical ventilation in Japan

Extracorporeal Membrane Oxygenation and Continuous Kidney Replacement Therapy: Technology and Outcomes - A Narrative Review.

The number of patients using critical care is increasing as our populations live longer thanks to advances in medical therapies. This is reflected by an increase in both usage and number of critical care beds as compared with total hospital beds across the United States. As this aging population suffers more and more from multiorgan dysfunction, including but not limited to respiratory failure, cardiac failure, and acute kidney injury, technologies are used to facilitate recovery in those that would have assuredly passed away years ago. Some of these advancements include extracorporeal membrane oxygenation and continuous kidney replacement therapy. In this article, we review the literature regarding the history, technology, indications, and outcomes of synchronous extracorporeal membrane oxygenation and kidney replacement therapy.

Discrete-Event Simulation Modeling of Critical Care Flow: New Hospital, Old Challenges.

As the demand for critical care beds rises each year, hospitals must be able to adapt. Delayed transfer of care reduces available critical care capacity and increases occupancy. The use of mathematic modeling within healthcare systems has the ability to aid planning of resources. Discrete-event simulation models can determine the optimal number of critical care beds required and simulate different what-if scenarios. Complex discrete-event simulation model was developed using a warm-up period of 30 days and ran for 30 trials against a 2-year period with the mean calculated for the runs. A variety of different scenarios were investigated to determine the effects of increasing capacity, increasing demand, and reduction of proportion and length of delayed transfer of care out of the ICU. Combined data from two ICUs in United Kingdom. The model was developed using 1,728 patient records and was validated against an independent dataset of 2,650 patients. None. During model validation, the average bed utilization and admittance rate were equal to the real-world data. In the what-if scenarios, we found that increasing bed numbers from 23 to 28 keeping the arrival rate stable reduces the average occupancy rate to 70%. We found that the projected 4% yearly increase in admissions could overwhelm even the 28-bedded unit, without change in the delayed transfer of care episodes. Reduction in the proportion of patients experiencing delayed transfer of care had the biggest effect on occupancy rates, time spent at full capacity, and average bed utilization. Using discrete-event simulation of commonly available baseline patient flow and patient care data produces reproducible models. Reducing the proportion of patients with delayed transfer of care had a greater effect in reducing occupancy levels than simply increasing bed numbers even when demand is increased.

Critical Care Bed Capacity in Asian Countries and Regions.

To assess the number of adult critical care beds in Asian countries and regions in relation to population size. Cross-sectional observational study. Twenty-three Asian countries and regions, covering 92.1% of the continent's population. Ten low-income and lower-middle-income economies, five upper-middle-income economies, and eight high-income economies according to the World Bank classification. Data closest to 2017 on critical care beds, including ICU and intermediate care unit beds, were obtained through multiple means, including government sources, national critical care societies, colleges, or registries, personal contacts, and extrapolation of data. Cumulatively, there were 3.6 critical care beds per 100,000 population. The median number of critical care beds per 100,000 population per country and region was significantly lower in low- and lower-middle-income economies (2.3; interquartile range, 1.4-2.7) than in upper-middle-income economies (4.6; interquartile range, 3.5-15.9) and high-income economies (12.3; interquartile range, 8.1-20.8) (p = 0.001), with a large variation even across countries and regions of the same World Bank income classification. This number was independently predicted by the World Bank income classification on multivariable analysis, and significantly correlated with the number of acute hospital beds per 100,000 population (r = 0.19; p = 0.047), the universal health coverage service coverage index (r = 0.35; p = 0.003), and the Human Development Index (r = 0.40; p = 0.001) on univariable analysis. Critical care bed capacity varies widely across Asia and is significantly lower in low- and lower-middle-income than in upper-middle-income and high-income countries and regions.

Certified and Advanced Degree Critical Care Nurses Improve Patient Outcomes.

The need for highly skilled and knowledgeable critical care nurses continues to evolve today and will in the future. Demands in critical care medicine for nurses with advanced degrees (master's in nursing: clinical nurse specialist; or doctorate in nursing: doctorate of philosophy in nursing or doctor of nursing practice) working in intensive care units or progressive care units can help meet these challenges. Nurses with certification and advanced degrees in nursing can be employed to work in 1 or combined roles such as nurse leaders and nurse researcher or intermittently fulfill roles as bedside nurses. These nurses working in critical care units have the ability to provide expertise that extends to staff, families, as well as patients. In addition, they are positioned to conduct relevant clinical research for evidence-based best practices. Evidence-based practice promotes excellence in nursing care and cost containment. Data on numbers of critical care beds in the United States increased 17% between 2000 and 2010.

Postoperative critical care and high-acuity care provision in the United Kingdom, Australia, and New Zealand

BackgroundDecisions to admit high-risk postoperative patients to critical care may be affected by resource availability. We aimed to quantify adult ICU/high-dependency unit (ICU/HDU) capacity in hospitals from the UK, Australia, and New Zealand (NZ), and to identify and describe additional ‘high-acuity’ beds capable of managing high-risk patients outside the ICU/HDU environment. MethodsWe used a modified Delphi consensus method to design a survey that was disseminated via investigator networks in the UK, Australia, and NZ. Hospital- and ward-level data were collected, including bed numbers, tertiary services offered, presence of an emergency department, ward staffing levels, and the availability of critical care facilities. ResultsWe received responses from 257 UK (response rate: 97.7%), 35 Australian (response rate: 32.7%), and 17 NZ (response rate: 94.4%) hospitals (total 309). Of these hospitals, 91.6% reported on-site ICU or HDU facilities. UK hospitals reported fewer critical care beds per 100 hospital beds (median=2.7) compared with Australia (median=3.7) and NZ (median=3.5). Additionally, 31.1% of hospitals reported having high-acuity beds to which high-risk patients were admitted for postoperative management, in addition to standard ICU/HDU facilities. The estimated numbers of critical care beds per 100 000 population were 9.3, 14.1, and 9.1 in the UK, Australia, and NZ, respectively. The estimated per capita high-acuity bed capacities per 100 000 population were 1.2, 3.8, and 6.4 in the UK, Australia, and NZ, respectively. ConclusionsPostoperative critical care resources differ in the UK, Australia, and NZ. High-acuity beds may have developed to augment the capacity to deliver postoperative critical care.

An assessment of critical care capacity in the Gambia

PurposeCritical illnesses are a major cause of morbidity and mortality in The Gambia, yet national data on critical care capacity is lacking. Materials and methodsWe surveyed eight of the eleven government-owned health facilities providing secondary and tertiary care in The Gambia's public health sector. At each hospital, a designated respondent completed a questionnaire reporting information on the presence of an intensive care unit, the number of critical care beds where available, monitoring equipment, and the ability to provide basic critical care services at their respective hospitals. ResultsThe response rate was 88% (7/8 hospitals). Only one hospital had a dedicated intensive care unit with eight ICU beds, resulting in an estimated 0.4 ICU beds/100,000 population in the country. All hospitals reported treating more than 50 critically ill patients a month, with trauma, obstetric emergencies, hypertensive emergencies and stroke accounting for the leading causes of admission respectively. The country lacks any trained specialists and resources to diagnose and treat critically ill patients. ConclusionsThe Gambia has a very low ICU bed capacity and lacks the human resources and equipment necessary to diagnose and treat the large number of critically ill patients admitted to public hospitals in the country.

Critically Ill Obstetric Patients in a General Critical Care Unit: A 5 Years' Retrospective Study in a Public Teaching Hospital of Eastern India.

Background:Critical care services are essential for the subset of obstetric patients suffering from severe maternal morbidity. Studies on obstetric critical care are important for benchmarking the issues which need to be addressed while managing critically ill obstetric patients. Although there are several published studies on obstetric critical care from India and abroad, studies from Eastern India are limited. The present study was conducted to fill in this lacuna and to audit the obstetric critical care admissions over a 5 years’ period.Settings and Design:Retrospective cohort study conducted in the general critical care unit (CCU) of a government teaching hospital.Materials and Methods:The records of all obstetric patients managed in the CCU over a span of 5 years (January 2011-December 2015) were analyzed.Results:During the study, 205 obstetric patients were admitted with a CCU admission rate of 2.1 per 1000 deliveries. Obstetric hemorrhage (34.64%) was the most common primary diagnosis among them followed by pregnancy-induced hypertension (26.83%). Severe hemorrhage leading to organ failure (40.48%) was the main direct indication of admission. Invasive ventilation was needed in 75.61% patients, and overall obstetric mortality rate was 33.66%. The median duration (in days) of invasive ventilation was 2 (interquartile range [IQR] 1-7), and the median length of CCU stay (in days) was 5 (IQR 3-9).Conclusions:Adequate number of critical care beds, a dedicated obstetric high dependency unit, and effective coordination between critical care and maternity services may prove helpful in high volume obstetric centers.

Trauma anaesthesia and critical care: the post trauma network era

Trauma forms a core component of the curriculum for both the Royal College of Anaesthetists (RCA) and Faculty of Intensive Care Medicine (FICM) because of the role that anaesthetists have in the management of every stage of major trauma, from point of injury to rehabilitation. Major trauma is defined as an injury severity score (ISS) .15, although this is not a clear cut-off and the injury pattern itself also has a bearing on the survivability. (Calculation of the ISS is shown in Table 1). The commonest cause of major trauma in the UK is road traffic collisions, resulting in .20 000 cases and 5400 deaths. In 2000, the Royal College of Surgeons recommended that major trauma should be organized into networks, with smaller units acting as feeder hospitals for major trauma centres. It further suggested that each region needed a major trauma plan, defining a definitive pathway for severely injured patients; including ambulance protocols, hospital capabilities, and interhospital transfer guidelines. A 2008 National Health Service review concluded that the arguments for major trauma centres were compelling. This in turn led to the appointment of a national clinical director of trauma in 2009 and the formulation of a Department of Health (DoH) regional trauma networks programme. They recommended that to maintain major trauma credentials, a hospital needs to see .650 major trauma cases per year. The London Trauma System commenced on April 1, 2011 and many other regions in the UK have or are currently developing their own systems. It is recognized that currently some regions do not have all acute surgical specialities represented requiring cross network cooperation to ensure equal access to treatment for time-critical interventions. In the 2000–2009 time period, the numbers of critical care beds in England increased by .1300 but capacity issues remain and ICNARC data indicate that only two-thirds of critical care moves in trauma patients are for clinical reasons. Pre-hospital care

The variability of critical care bed numbers in Europe

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 could provide data on numbers of critical care beds (intensive care and intermediate care). These data were then cross-referenced with data from international databases describing population size and age, gross domestic product (GDP), expenditure on healthcare and numbers of acute care beds. We identified 2,068,892 acute care beds and 73,585 (2.8 %) critical care beds. Due to the heterogeneous descriptions of these beds in the individual countries it was not possible to discriminate between intensive care and intermediate care in most cases. On average there were 11.5 critical care beds per 100,000 head of population, with marked differences between countries (Germany 29.2, Portugal 4.2). The numbers of critical care beds per country corrected for population size were positively correlated with GDP (r(2) = 0.16, p = 0.05), numbers of acute care beds corrected for population (r(2) = 0.12, p = 0.05) and the percentage of acute care beds designated as critical care (r(2) = 0.59, p < 0.0001). They were not correlated with the proportion of GDP expended on healthcare. Critical care bed numbers vary considerably between countries in Europe. Better understanding of these numbers should facilitate improved planning for critical care capacity and utilization in the future.

‘The future ain’t what it used to be’– reflections on the evolution of anaesthesia

‘The future ain’t what it used to be’– reflections on the evolution of anaesthesia

Factors Influencing the Volume-Outcome Relationship in Gastrectomies: A Population-Based Study

A relationship between hospital procedural volume and patient outcomes has been observed in gastrectomies for primary gastric cancer, but modifiable factors influencing this relationship are not well elaborated. We performed a population-based study of 1864 patients undergoing gastrectomy for primary gastric cancers at 214 hospitals. Hospitals were stratified as high-, intermediate-, or low-volume centers. Multivariate models were constructed to evaluate the effect of institutional procedural volume and other hospital- and patient-specific factors on the risk of in-hospital mortality, adverse events, and failure to rescue, defined as mortality after an adverse event. High-volume centers attained an in-hospital mortality rate of 1.0% and failure-to-rescue rate of .7%, both less than one-fifth of that seen at intermediate- and low-volume centers, although adverse event rates were similar across the three volume tiers. In multivariate modeling, treatment at a high-volume hospital decreased the odds of mortality (odds ratio [OR], .22; 95% confidence interval [95% CI], .05-.89), whereas treatment at an institution with a high ratio of licensed vocational nurses per bed increased the odds of mortality (OR, 1.96; 95% CI, 1.04-3.75). Being treated at a hospital with a greater than median number of critical care beds decreased odds of mortality (OR, .46; 95% CI, .25-.81) and failure to rescue (OR, .53; 95% CI, .29-.97). Undergoing gastrectomy at a high-volume center is associated with lower in-hospital mortality. However, improving the rates of mortality after adverse events and reevaluating nurse staffing ratios may provide avenues by which lower-volume centers can improve mortality rates.

The Changing Epidemiology of Mechanical Ventilation: A Population-Based Study

The number of critical care beds in the United States has been increasing considerably, but it is unclear how these additional beds have been used. Mechanical ventilation for acute respiratory failure almost always demands ICU care and is likely to be a reliable indicator of critical care resource requirements on a population level. The objective of this study was to measure changes in the yearly incidence of mechanical ventilation in a statewide population. The North Carolina Hospital Discharge Database contains data on all discharges from nonfederal, nonpsychiatric hospitals in North Carolina. Authors extracted data on adult patients with International Classification of Diseases, 9th Revision, Clinical Modification procedure codes for mechanical ventilation from 1996 to 2002. The incidence of mechanical ventilation for adults grew from 284/100,000 population in 1996 to 314/100,000 in 2002, an increase of 11% (P < .05). While patients aged >64 had the highest age-specific incidence of mechanical ventilation each year, the greatest increase in incidence occurred in younger age groups (19% increase for age 18-64 vs 4% increase for age >64). The mean Charlson score increased from 1.76 +/- 1.73 to 1.89 +/- 1.86 (P < .001). Renal disease became more prevalent among patients requiring mechanical ventilation (17% of patients in 1996 vs 24% in 2002). Hospital charges adjusted for the medical consumer price index increased by 12%. The proportion of patients discharged to home declined from 45.4% to 34.4%, and discharges to nursing homes grew from 7.3% to 10.7%. The incidence of mechanical ventilation is increasing, and the increase is associated with a higher burden of comorbidities and fewer discharges to home.

Intensivist-to-Bed Ratio: Association With Outcomes in the Medical ICU

With an increasing number of critical care beds, a shortage of critical care physicians, and pressure from purchasers, there is a need to define the optimal intensivist-to-ICU bed ratio. The objective of this study was to determine if there are any associations between the intensivist-to-ICU bed ratio and the outcome of patients admitted to the medical ICU.Retrospective cohort study.A tertiary care medical center.All critically ill patients admitted to a medical ICU between December 8, 2001, and July 14, 2003.None.Demographics, APACHE (acute physiology and chronic health evaluation) III-predicted mortality, ICU length of stay (LOS), hospital LOS, and ICU and hospital mortality rates. Four time periods based on intensivist-to-ICU bed ratios of 1:7.5, 1:9.5, 1:12, and 1:15 were identified. Regression analyses were performed to develop customized models to predict ICU and hospital LOS and mortality. The ICU LOS ratio, defined as the ratio of the observed to predicted LOS, and standardized mortality ratio (SMR) were calculated for each of the four periods.A total of 2,492 patients were included in the study. There was no difference in the severity of illness at the time of ICU admission among the four periods. The mean ICU LOS ratio was longer for an intensivist-to-ICU bed ratio of 1:15 compared to the other periods. The ICU and hospital SMR did not differ significantly among the four periods.Differences in intensivist-to-ICU bed ratios, ranging from 1:7.5 to 1:15, were not associated with differences in ICU or hospital mortality. However, a ratio of 1:15 was associated with increased ICU LOS.

The management of severe burns in children

Outcome after burn injuries in children has substantially improved over the last few decades. Survival following burns of 100% surface area is now possible. All paediatric burns, regardless of size, should be considered candidates for treatment. Scalds are still a common childhood injury, but with new biological dressings they are not always the irreversible disfiguring injuries of the past. Four important and unresolved issues in paediatric burn care in the UK are: (1) the care of burned children in hospitals without burns teams; (2) inadequate numbers of critical care beds for children with burns; (3) morbidity after small burns (toxic shock syndrome is still leading to death in some children); and (4) the complete lack of a rehabilitation service for burn-injured children. This review will look at the demographics of burn injury in children, as well as current surgical and non-surgical therapies for these children. It will also consider ethical and political issues.

Absence of ageism in access to critical care: a cross-sectional study.

in recent years, the NHS has been accused of ageism frequently and from many fronts. Previous studies have shown that the number of critical care beds in the UK is inadequate to meet the needs of the population. This study asks whether there is discrimination against older people in access to these critical care beds. all sick patients in five hospitals in a South Wales Health Authority were studied every 12th day for one calendar year. Demographic, clinical and physiological data were collected. Ten members of the Welsh Intensive Care Society subsequently judged the optimum location of care for each of these individuals. This was based on a summary of diagnoses, procedures and physiological/biochemical results, but without access to the age of the patient or type of ward or hospital where the patients was actually treated. These data were analysed to determine whether the likelihood of being treated in the most appropriate setting, based on the consensus decision, was influenced by the patient's age. 4058 patients met the study criteria, of whom 2287 patients (56.4% of the total) were being cared for on a general ward and 1769 in critical care areas. The intensivist panel determined that 1085 (53%) ward based patients were more suitable for care on intensive care or high dependency units and 220 (12.4%) critical care patients were suitable for ward care. The proportion of patients considered to be in an inappropriate ward varied little in different age groups. many patients on general wards have needs that may be more appropriately addressed on critical care units but there is no relationship between these unmet needs and the age of the patient.