Forecasting Hospital Room and Ward Occupancy Using Static and Dynamic Information Concurrently: Retrospective Single-Center Cohort Study.

BACKGROUND: Predicting the bed occupancy rate (BOR) is essential for efficient hospital resource management, long-term budget planning, and patient care planning. Although macro-level BOR prediction for the entire hospital is crucial, predicting occupancy at a detailed level, such as specific wards and rooms, is more practical and useful for hospital scheduling. OBJECTIVE: The aim of this study was to develop a web-based support tool that allows hospital administrators to grasp the BOR for each ward and room according to different time periods. METHODS: We trained time-series models based on long short-term memory (LSTM) using individual bed data aggregated hourly each day to predict the BOR for each ward and room in the hospital. Ward training involved 2 models with 7- and 30-day time windows, and room training involved models with 3- and 7-day time windows for shorter-term planning. To further improve prediction performance, we added 2 models trained by concatenating dynamic data with static data representing room-specific details. RESULTS: We confirmed the results of a total of 12 models using bidirectional long short-term memory (Bi-LSTM) and LSTM, and the model based on Bi-LSTM showed better performance. The ward-level prediction model had a mean absolute error (MAE) of 0.067, mean square error (MSE) of 0.009, root mean square error (RMSE) of 0.094, and R2 score of 0.544. Among the room-level prediction models, the model that combined static data exhibited superior performance, with a MAE of 0.129, MSE of 0.050, RMSE of 0.227, and R2 score of 0.600. Model results can be displayed on an electronic dashboard for easy access via the web. CONCLUSIONS: We have proposed predictive BOR models for individual wards and rooms that demonstrate high performance. The results can be visualized through a web-based dashboard, aiding hospital administrators in bed operation planning. This contributes to resource optimization and the reduction of hospital resource use.

Hospital bed capacity across in Tunisia hospital during the first 4 waves of the COVID-19 pandemic: A descriptive analysis.

Background: In March 2020, the WHO declared COVID-19 as a pandemic, and Tunisia implemented a containment and targeted screening strategy. The country's public health policy has since focused on managing hospital beds. Methods: The study analyzed the bed occupancy rates in public hospitals in Tunisia during the pandemic. The evolution of daily cases and nonpharmaceutical interventions (NPI) actions undertaken by the Tunisian Government were also analyzed. The study used 3 indices to assess bed flexibility: Ramp duration until the peak, ramp growth until the peak, and ramp rate until the peak. The study also calculated the time shift at the start and peak of each wave to evaluate the government's response efficacy. Results: The study found that the evolution of the epidemic in Tunisia had 2 phases. The first phase saw the pandemic being controlled due to strong NPI actions, while the second phase saw a relaxation of measures and an increase in wave intensity. ICU bed availability followed the demand for beds, but ICU bed occupancy remained high, with a maximum of 97%. The government's response in terms of bed distribution and reallocation was slow. The study found that the most deadly wave by ICU occupied bed was the third wave due to a historical variant, while the fifth wave due to the delta variant was the most deadly in terms of cumulative death. Conclusions: The study concluded that decision-makers could use its findings to assess their response capabilities in the current pandemic and future ones. The study highlighted the importance of flexible and responsive healthcare systems in managing pandemics.

Progressive Relationship Between Sustainable Development of Elderly Care Institutions and Spatial Environmental Factors: A Study Based on the Influence of Supermarkets, Medical Accessibility, and Parks in Urban Areas.

Purpose: To study the relationship between three variables, namely, the number of supermarkets around, the average distance to medical institutions designated to be covered by basic medical insurance, and the presence of parks around, and the sustainable development of elderly care institutions. Patients and Methods: This paper is based on the census database of elderly care institutions in Beijing. We ran a self-developed Python program to mine the database after adding three variables, namely, the number of supermarkets around, the average distance to medical institutions designated to be covered by basic medical insurance (hereinafter referred to as "designated medical institutions"), and the presence of parks around, and then used the least squares method in regression analysis. Results: The number of years of depreciation for fixed assets had some degree of influence on the occupancy rate of an elderly care institution under sustained operation. The occupancy rate of above 80% was efficient for an elderly care institution. There was a progressive relationship between the external spatial factors and the internal resources of an elderly care institution in terms of influencing the occupancy rate of the institution. Optimizing the spatial distribution of elderly care institutions should first optimize the choice of location. Conclusion: The occupancy rate of an elderly care institution was closely related to the convenience of living conditions and that site selection was crucial for such a facility. We arrived at two recommendations for the future development of elderly care institutions, 1. Reducing the number of the institutions in areas with unfavorable geographic positions and serving senior care needs within an appropriate close distance, so as to better optimize the spatial distribution of senior care facilities, improve the efficiency of resource allocation. 2. Strike a balance between the economic benefits of operating entities and the social benefits associated with older people.

Difference in determinants of ICU admission and death among COVID-19 hospitalized patients in two epidemic waves in Portugal: possible impact of healthcare burden and hospital bed occupancy on clinical management and outcomes, March-December 2020.

Aim: Identify factors associated with COVID-19 intensive care unit (ICU) admission and death among hospitalized cases in Portugal, and variations from the first to the second wave in Portugal, March-December 2020. Introduction: Determinants of ICU admission and death for COVID-19 need further understanding and may change over time. We used hospital discharge data (ICD-10 diagnosis-related groups) to identify factors associated with COVID-19 outcomes in two epidemic periods with different hospital burdens to inform policy and practice. Methods: We conducted a retrospective cohort study including all hospitalized cases of laboratory-confirmed COVID-19 in the Portuguese NHS hospitals, discharged from March to December 2020. We calculated sex, age, comorbidities, attack rates by period, and calculated adjusted relative risks (aRR) for the outcomes of admission to ICU and death, using Poisson regressions. We tested effect modification between two distinct pandemic periods (March-September/October-December) with lower and higher hospital burden, in other determinants. Results: Of 18,105 COVID-19 hospitalized cases, 10.22% were admitted to the ICU and 20.28% died in hospital before discharge. Being aged 60-69 years (when compared with those aged 0-49) was the strongest independent risk factor for ICU admission (aRR 1.91, 95%CI 1.62-2.26). Unlike ICU admission, risk of death increased continuously with age and in the presence of specific comorbidities. Overall, the probability of ICU admission was reduced in the second period but the risk of death did not change. Risk factors for ICU admission and death differed by epidemic period. Testing interactions, in the period with high hospital burden, those aged 80-89, women, and those with specific comorbidities had a significantly lower aRR for ICU admission. Risk of death increased in the second period for those with dementia and diabetes. Discussion and conclusions: The probability of ICU admission was reduced in the second period. Different patient profiles were identified for ICU and deaths among COVID-19-hospitalized patients in different pandemic periods with lower and higher hospital burden, possibly implying changes in clinical practice, priority setting, or clinical presentation that should be further investigated and discussed considering impacts of higher burden on services in health outcomes, to inform preparedness, healthcare workforce planning, and pandemic prevention measures.

Gerenciamento de Leitos: do Planejamento à Implementação em um Serviço Hospitalar / Hospital bed management: from planning to implementation in a hospital service

Objetivo: A falta de leitos hospitalares no Brasil é queixa comum entre usuários do Sistema Único de Saúde. Objetivo: Relatar a experiência da construção de um Serviço de Gerenciamento de leitos e apresentar a atuação do enfermeiro como gestor, em prol da visibilidade e fortalecimento da classe de enfermagem. Método: Relato de experiência da implementação da gestão de leitos de um hospital público estadual de médio porte, em um município do interior do estado de São Paulo. Resultado: A partir da implantação houve mudanças no perfil dos indicadores dos setores assistencias, com a utilização dos leitos aproveitados em sua capacidade máxima. Observou-se a diminuição da fila de espera para internação em consequência do acesso oportuno e ordenado à vaga. Conclusão: Pode-se inferir que o gerenciamento de leitos é efetivo e eficiente na gestão hospitalar com resultados operacionais e financeiros satisfatórios e um fator preponderante para a segurança e satisfação dos clientes.(AU)

Objective: The lack of hospital beds in Brazil is a common complaint among users of the Unified Health System. Objective: To report the experience of the construction of a Bed Management Service and to present the nurse's role as manager, for the visibility and strengthening of the nursing class. Method: Experience report of the implementation of bed management in a public hospital of medium size, in a city in the interior of the state of São Paulo. Result: From the implementation there were changes in the profile of the indicators of the care sectors, with the use of beds used to their maximum capacity. A reduction in the waiting list for hospitalization was observed as a result of the timely and orderly access to vacancies. Conclusion: It can be inferred that the management of beds is effective and efficient in hospital management with satisfactory operational and financial results and a preponderant factor for the customers' safety and satisfaction.(AU)

Objetivo: La falta de camas hospitalarias en Brasil es una queja común entre los usuarios del Sistema Único de Salud. Objetivo: Relatar la experiencia de la construcción de un Servicio de Gestión de camas y presentar la actuación de la enfermera como gestora, para la visibilidad y fortalecimiento de la clase de enfermería. Método: Relato de experiência da implementação da gestão de lechos de um hospital público estadual de médio porte, em um município do interior do estado de São Paulo. Resultado: A partir da implementação houve mudanças no perfil dos indicadores dos setores assistência, com o uso de camas utilizadas ao seu máximo de capacidade. Observou-se a diminuição da fila de espera para internação em consequência do acesso oportuno e ordenado à vaga. Conclusão: É possível inferir que a gestão de camas é eficaz e eficiente na gestão hospitalar com resultados operacionais e financeiros satisfatórios e um factor preponderante para a segurança e satisfação dos clientes.(AU)

EFFECTIVENESS OF USING THE BED FUND AND HUMAN RESOURCES FOR PROVIDING MEDICAL CARE TO CHILDREN WITH RESPIRATORY DISEASES.

OBJECTIVE: The aim: Retrospectively evaluate the effectiveness of the use of beds and human resources for the treatment of children with respiratory diseases in hospitals in the period 2008-2021. PATIENTS AND METHODS: Materials and methods: We calculated indicators that characterize the efficiency of the use of bed and personnel resources: the density of beds per 10,000, the rate of hospitalized children per 10,000 (RH per 10,000), the bed occupancy rate per year (BOR), average length of stay (ALOS), full-time positions (FTP) per 100,000, number of beds per 1 FTP of doctors. RESULTS: Results: During 2008-2021, there was a significant decrease in the density of all types of beds. The percentage of hospitalized children for inpatient treatment decreased, BOR decreased, and ALOS decreased. The density of full-time positions of allergists increased by +23.78%, pediatricians by +4.86%, pulmonologists decreased by -13.15%. In 2021, there were 10.31 beds for 1 FTP of an allergist, 12.8 beds for 1 FTP of a pulmonologist, and 5.83 beds for 1 FTP of a pediatrician. According to the correlation matrix, it was established that the more beds there are for 1 full-time position of a pediatrician and 1 full-time position of an allergist, the longer the ALOS and the bed occupancy rate are. CONCLUSION: Conclusions: When planning staffing of health care institutions, it is necessary to mind the level of urbanization of the region, and ensure status of the general practitioner as a leading medical specialist responsible for medical care during the first meeting with the patient and his subsequent follow-up.

Stressed systems: Stroke unit bed occupancy and impact on reperfusion therapy in acute ischemic stroke.

Objectives: We observed a decrease in the number of patients who were offered reperfusion therapy. We aimed to investigate if whether hospital system pressure measured as the percentage of stroke bed occupancy influenced decisions on treatment and disposition. Design: Data from a regional quality of stroke care database were obtained and linked to the organizational data monitoring of the hourly inpatient stroke bed occupancy rate. Logistic regression was used to analyze the relationship. Results: A total of 15,025 admissions were included from 1 January 2019 to 24 August 2022. Of these, 5,659 (38%) had an acute ischemic stroke. The rates of reperfusion therapy treatment were the highest in 2019 (36.2%) and 2020 (34.1%) and declined afterward (30.0% in 2021). In the logistic regression analysis, an occupancy rate of ≥85% in the hour of the first admission was associated with reduced odds of admission at the stroke unit within 3 h from the symptom onset [adjusted odds ratio: 0.80, 95% confidence interval: (0.71-0.90), p < 0.001] and a reduced odds of receiving reperfusion therapy (adjusted odds ratio: 0.83 (0.73-0.95), p = 0.007). Conclusion: An increased bed occupancy level in the hour of the first hospital admission for stroke patients was strongly associated with decreased odds of receiving reperfusion therapy.

Estimating the impact of influenza vaccination of low-risk 50-64-year-olds on acute and ICU hospital bed usage in an influenza season under endemic COVID-19 in the UK.

Co-circulation of influenza and SARS-CoV-2 has the potential to place considerable strain on health-care services. We estimate the cost-effectiveness and health-care resource utilization impacts of influenza vaccination of low-risk 50-64-y-olds in the United Kingdom (UK) against a background SARS-CoV-2 circulation. A dynamic susceptible-exposed-infected-recovered model was used to simulate influenza transmission, with varying rates of vaccine coverage in the low-risk 50-64 y age-group. Four scenarios were evaluated: no vaccination (baseline), 40%, 50%, and 60% coverage. For the 50% and 60% coverage, this rate was also applied to high-risk 50-64-y-olds, whereas 48.6% was used for the baseline and 40% coverage scenarios. Cost-effectiveness was estimated in terms of humanistic outcomes and incremental cost-effectiveness ratio (ICER), with discounting applied at 3%. Overall, influenza vaccination of 50-64-y-olds resulted in reductions in GP visits, hospitalizations, and deaths, with a reduction in influenza-related mortality of 34%, 41%, and 52% for 40%, 50%, and 60% coverage, respectively. All four scenarios resulted in acute and intensive care unit (ICU) bed occupancy levels above available capacity, although vaccination of low-risk 50-64-y-olds resulted in a 35-54% and 16-25% decrease in excess acute and ICU bed requirements, respectively. Vaccination of this group against influenza was highly cost-effective from the payer perspective, with ICERs of £2,200-£2,343/quality-adjusted life year across the coverage rates evaluated. In conclusion, in the UK, vaccination of low-risk 50-64-y-olds against influenza is cost-effective and can aid in alleviating bed shortages in a situation where influenza and SARS-CoV-2 are co-circulating.

Prediction of hospitalisations based on wastewater-based SARS-CoV-2 epidemiology.

Wastewater-based epidemiology is widely applied in Austria since April 2020 to monitor the SARS-CoV-2 pandemic. With a steadily increasing number of monitored wastewater facilities, 123 plants covering roughly 70 % of the 9 million population were monitored as of August 2022. In this study, the SARS-CoV-2 viral concentrations in raw sewage were analysed to infer short-term hospitalisation occupancy. The temporal lead of wastewater-based epidemiological time series over hospitalisation occupancy levels facilitates the construction of forecast models. Data pre-processing techniques are presented, including the approach of comparing multiple decentralised wastewater signals with aggregated and centralised clinical data. Time­lead quantification was performed using cross-correlation analysis and coefficient of determination optimisation approaches. Multivariate regression models were successfully applied to infer hospitalisation bed occupancy. The results show a predictive potential of viral loads in sewage towards Covid-19 hospitalisation occupancy, with an average lead time towards ICU and non-ICU bed occupancy between 14.8-17.7 days and 8.6-11.6 days, respectively. The presented procedure provides access to the trend and tipping point behaviour of pandemic dynamics and allows the prediction of short-term demand for public health services. The results showed an increase in forecast accuracy with an increase in the number of monitored wastewater treatment plants. Trained models are sensitive to changing variant types and require recalibration of model parameters, likely caused by immunity by vaccination and/or infection. The utilised approach displays a practical and rapidly implementable application of wastewater-based epidemiology to infer hospitalisation occupancy.

Hospitalización a domicilio para pacientes quirúrgicos ante una pandemia por SARS-CoV-2: nuestra experiencia / Hospitalization at home for surgical patients in the face of a SARS-CoV-2 pandemic: our experience

Introducción: La hospitalización a domicilio para pacientes quirúrgicos (HaDQ) es una al-ternativa a la hospitalización convencional para pacientes quirúrgicos estables clínicamente, que precisen procedimientos de enfermería complejos por intensidad, frecuencia o carac-terísticas, y control por especialista quirúrgico en el domicilio.Método: Estudio transversal, descriptivo y retrospectivo de la actividad de la HADQ de nuestro hospital durante los primeros seis me-ses del 2020, para analizar la repercusión de la pandemia por SARS-CoV-2 en la unidad. Se distinguen tres periodos: prepandemia (enero-febreo), confinamiento (marzo-abril), poscon-finamiento (mayo-junio). Se diferencian dos grupos: A (HaD convencional) y B (despistaje preoperatorio COVID19). Se recogieron diver-sas variables: mes, tipo, estancia (HaD y hospi-tal), procedimientos, reingresos, domicilio, tipo visitas, COVID+. Se realizó un análisis estadís-tico descriptivo cuantitativo y cualitativo de los resultados obtenidosResultados: Ingresaron 345 pacientes, 225 en el grupo A (fase Pre (34%), fase C (40%), y fase Pos (25%)), y 120 en el B (fase C (75%), fase Pos (25%)). El confinamiento (fase C) fue el pe-ríodo más activo de la HADQ, tanto por número de ingresos (53%), como por la complejidad del grupo A que requería más procedimientos (71%) y más visitas domiciliarias (52%). Tam-bién aumentaron los pacientes de zona de no cobertura (42%), que implicaron visitas médicas y de enfermería en Hospital de Día (HD) (21%), y aumento de consultas telefónicas médicas (36%). En la fase Pos disminuyeron un 37% los ingresos del grupo A.Conclusiones: La HaDQ se reorganizó por la pandemia para atender a más pacientes quirúr-gicos, siendo un recurso asistencial esencial, especialmente durante el confinamiento. (AU)

Introduction: The HaDQ is an alternative to conventional hospitalization for clinically stable surgical patients who require complex nursing procedures due to intensity, frequency or char-acteristics, and control by a surgical specialist at home.Method: Cross-sectional, descriptive and ret-rospective study of the HADQ activity of our hospital during the first six months of 2020, to analyze the impact of the SARSCov2 pandemic in the unit. Three periods are distinguished: pre-pandemic (Jan-Feb), lockdown (Mar-Apr), post-lockdown (May-Jun). Two groups are differen-tiated: A (conventional HaD) and B (COVID19 preoperative screening). Various variables were collected: month, type, stay (HaD and hospi-tal), procedures, readmissions, address, type of visits, covid+. A quantitative and qualitative descriptive statistical analysis of the results ob-tained was carried out.Results: 345 patients were admitted, 225 in group A (phase Pre (34%), Phase C (40%), and phase Post (25%)), and 120 in group B (Phase C (75%), phase Post (25%)). %)). The confinement (phase C) was the most active period of the HADQ, both due to the number of admissions (53%), and the complexity of group A, which re-quired more procedures (71%) and more home visits (52%). There was also an increase in pa-tients from the non-coverage area (42%), which involved medical and nursing visits at the Day Hospital (HD) (21%), and an increase in medi-cal telephone consultations (36%). In the phase Post, the income of group A decreased by 37%.Conclusions: The HaDQ was reorganized due to the pandemic to care for more surgical pa-tients, being an essential care resource, espe-cially during confinement. (AU)

The association between bed occupancy rates and hospital quality in the English National Health Service.

We study whether hospitals that exhibit systematically higher bed occupancy rates are associated with lower quality in England over 2010/11-2017/18. We develop an economic conceptual framework to guide our empirical analysis and run regressions to inform possible policy interventions. First, we run a pooled OLS regression to test if high bed occupancy is associated with, and therefore acts as a signal of, lower quality, which could trigger additional regulation. Second, we test whether this association is explained by exogenous demand-supply factors such as potential demand, and unavoidable costs. Third, we include determinants of bed occupancy (beds, length of stay, and volume) that might be associated with quality directly, rather than indirectly through bed occupancy. Last, we use a within-between random-effects specification to decompose these associations into those due to variations in characteristics between hospitals and variations within hospitals. We find that bed occupancy rates are positively associated with overall and surgical mortality, negatively associated with patient-reported health gains, but not associated with other indicators. These results are robust to controlling for demand-supply shifters, beds, and volume. The associations reduce by 12%-25% after controlling for length of stay in most cases and are explained by variations in bed occupancy between hospitals.

Modeling COVID-19 hospital admissions and occupancy in the Netherlands.

We describe the models we built for predicting hospital admissions and bed occupancy of COVID-19 patients in the Netherlands. These models were used to make short-term decisions about transfers of patients between regions and for long-term policy making. For forecasting admissions we developed a new technique using linear programming. To predict occupancy we fitted residual lengths of stay and used results from queueing theory. Our models increased the accuracy of and trust in the predictions and helped manage the pandemic, minimizing the impact in terms of beds and maximizing remaining capacity for other types of care.

[Forecasting models to guide intensive care COVID-19 capacities in Germany]. / Prognosemodelle zur Steuerung von intensivmedizinischen COVID-19-Kapazitäten in Deutschland.

BACKGROUND: Time-series forecasting models play a central role in guiding intensive care coronavirus disease 2019 (COVID-19) bed capacity in a pandemic. A key predictor of future intensive care unit (ICU) COVID-19 bed occupancy is the number of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in the general population, which in turn is highly associated with week-to-week variability, reporting delays, regional differences, number of unknown cases, time-dependent infection rates, vaccinations, SARS-CoV­2 virus variants, and nonpharmaceutical containment measures. Furthermore, current and also future COVID ICU occupancy is significantly influenced by ICU discharge and mortality rates. METHODS: Both the number of new SARS-CoV­2 infections in the general population and intensive care COVID-19 bed occupancy rates are recorded in Germany. These data are statistically analyzed on a daily basis using epidemic SEIR (susceptible, exposed, infection, recovered) models using ordinary differential equations and multiple regression models. RESULTS: Forecast results of the immediate trend (20-day forecast) of ICU occupancy by COVID-19 patients are made available to decision makers at various levels throughout the country. CONCLUSION: The forecasts are compared with the development of available ICU bed capacities in order to identify capacity limitations at an early stage and to enable short-term solutions to be made, such as supraregional transfers.

Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy.

This paper introduces mathematical models that support dynamic fair balancing of COVID-19 patients over hospitals in a region and across regions. Patient flow is captured in an infinite server queueing network. The dynamic fair balancing model within a region is a load balancing model incorporating a forecast of the bed occupancy, while across regions, it is a stochastic program taking into account scenarios of the future bed surpluses or shortages. Our dynamic fair balancing models yield decision rules for patient allocation to hospitals within the region and reallocation across regions based on safety levels and forecast bed surplus or bed shortage for each hospital or region. Input for the model is an accurate real-time forecast of the number of COVID-19 patients hospitalised in the ward and the Intensive Care Unit (ICU) of the hospitals based on the predicted inflow of patients, their Length of Stay and patient transfer probabilities among ward and ICU. The required data is obtained from the hospitals' data warehouses and regional infection data as recorded in the Netherlands. The algorithm is evaluated in Dutch regions for allocation of COVID-19 patients to hospitals within the region and reallocation across regions using data from the second COVID-19 peak.

Long Stay and Frequent Readmission in the Pediatric Intensive Care in The Netherlands; 15-Year Time Trends.

To describe time trends and the burden of long-stay patients (LSP) and frequent-readmission patients (FRP) in the PICUs in The Netherlands. DESIGN: Retrospective analysis of data from the nationwide Pediatric Intensive Care Evaluation registry including all PICU admissions in The Netherlands. SETTING: All PICUs in The Netherlands. PATIENTS: All PICU patients less than 18 years old admitted between 2003 and 2017. Two groups of patients were identified: LSP (admitted ≥30 d) and FRP (≥3 readmissions within the first year after their first admission). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 47,424 children were admitted on 59,759 occasions. LSP (3.3% of total cohort) and FRP (2.1%) accounted for 37.5% and 14.5% of cumulative admission days, respectively. Patients fulfilling both LSP and FRP criteria (0.6%) accounted for 9.9% of cumulative admission days. No significant time trends were observed between 2003 and 2017 for the number of LSP and FRP, nor for accounted cumulative admission days. Age and disease severity-adjusted mortality was significantly higher for LSP (odds ratio [OR], 2.16; 95% CI, 1.66-2.82; p < 0.001) and FRP OR 1.40 (95% CI, 0.97-2.01; p = 0.069) compared with the general PICU population. Overall PICU mortality decreased significantly between 2003 (6.5%) and 2017 (3.7%; p = 0.004), but remained constant over time for both LSP (17.2%) and FRP (6.3%). CONCLUSIONS: The proportion of LSP and FRP and their burden on PICU capacity are considerable and remained constant between 2003 and 2017. Whereas age and disease severity-adjusted mortality decreased in the general PICU population, it did not change in LSP and FRP.

Impact of the COVID-19 pandemic on critical care utilization in Japan: a nationwide inpatient database study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has disrupted critical care services worldwide. Examining how critical care systems responded to the COVID-19 pandemic on a national level will be useful in setting future critical care plans. The present study aimed to describe the utilization of critical care services before and during the COVID-19 pandemic using a nationwide Japanese inpatient administrative database. METHODS: All patients admitted to an intensive care unit (ICU) or a high-dependency care unit (HDU) from February 9, 2019, to February 8, 2021, in the Japanese Diagnosis Procedure Combination inpatient database were included. February 9, 2020, was used as the breakpoint separating the periods before and during COVID-19 pandemic. Hospital and patient characteristics were compared before and during the COVID-19 pandemic. Change in ICU and HDU bed occupancy before and during the COVID-19 pandemic was evaluated using interrupted time-series analysis. RESULTS: The number of ICU patients before and during the COVID-19 pandemic was 297,679 and 277,799, respectively, and the number of HDU patients was 408,005 and 384,647, respectively. In the participating hospitals (383 ICU-equipped hospitals and 460 HDU-equipped hospitals), the number of hospitals which increased the ICU and HDU beds capacity were 14 (3.7%) and 33 (7.2%), respectively. Patient characteristics and outcomes in ICU and HDU were similar before and during the COVID-19 pandemic except main etiology for admission of COVID-19. The mean ICU bed occupancy before and during the COVID-19 pandemic was 51.5% and 47.5%, respectively. The interrupted time-series analysis showed a downward level change in ICU bed occupancy during the COVID-19 pandemic (- 4.29%, 95% confidence intervals - 5.69 to - 2.88%), and HDU bed occupancy showed similar trends. Of 383 hospitals with ICUs, 232 (60.6%) treated COVID-19 patients in their ICUs. Their annual hospital case volume of COVID-19 ICU patients varied greatly, with a median of 10 (interquartile range 3-25, min 1, max 444). CONCLUSIONS: The ICU and HDU bed capacity did not increase while their bed occupancy decreased during the COVID-19 pandemic in Japan. There was no change in clinicians' decision-making to forego ICU/HDU care for selected patients, and there was no progress in the centralization of critically ill COVID-19 patients.

Recusa de leitos e triagem de pacientes admitidos nas unidades de terapia intensiva do Brasil: estudo transversal do tipo survey nacional / Refusal of beds and triage of patients admitted to intensive care units in Brazil: a cross-sectional national survey

RESUMO Objetivo: Conhecer dados sobre recusa de leitos nas unidades intensivas no Brasil, assim como avaliar o uso de sistemas de triagem pelos profissionais atuantes. Métodos: Estudo transversal do tipo survey. Com a metodologia Delphi, foi criado um questionário contemplando os objetivos do trabalho. Foram convidados médicos e enfermeiros inscritos na rede de pesquisa da Associação de Medicina Intensiva Brasileira (AMIBnet). Uma plataforma da web (SurveyMonkey®) foi a forma de aplicação do questionário. As variáveis deste trabalho foram mensuradas em categorias e expressas como proporção. Foram usados o teste do qui-quadrado ou o teste exato de Fisher, para verificar associações. O nível de significância foi de 5%. Resultados: No total, 231 profissionais responderam o questionário, representando todas as regiões do país. As unidades intensivas nacionais tinham mais de 90% de taxa de ocupação sempre ou frequentemente para 90,8% dos participantes. Dentre os participantes, 84,4% já deixaram de admitir pacientes em leito intensivo devido à lotação da unidade. Metade das instituições brasileiras (49,7%) não possuía protocolos de triagem de leitos intensivos instituídos. Conclusão: A recusa de leito pela alta taxa de ocupação é frequente nas unidades de terapia intensiva do Brasil. Ainda assim, metade dos serviços do Brasil não adota protocolos para triagem de leitos.

ABSTRACT Objective: To obtain data on bed refusal in intensive care units in Brazil and to evaluate the use of triage systems by professionals. Methods: A cross-sectional survey. Using the Delphi methodology, a questionnaire was created contemplating the objectives of the study. Physicians and nurses enrolled in the research network of the Associação de Medicina Intensiva Brasileira (AMIBnet) were invited to participate. A web platform (SurveyMonkey®) was used to distribute the questionnaire. The variables in this study were measured in categories and expressed as proportions. The chi-square test or Fisher's exact test was used to verify associations. The significance level was set at 5%. Results: In total, 231 professionals answered the questionnaire, representing all regions of the country. The national intensive care units had an occupancy rate of more than 90% always or frequently for 90.8% of the participants. Among the participants, 84.4% had already refused admitting patients to the intensive care unit due to the capacity of the unit. Half of the Brazilian institutions (49.7%) did not have triage protocols for admission to intensive beds. Conclusions: Bed refusal due to high occupancy rates is common in Brazilian intensive care units. Even so, half of the services in Brazil do not adopt protocols for triage of beds.

Economic Impact of the Implementation of an Enhanced Recovery after Surgery (ERAS) Protocol in a Bariatric Patient Undergoing a Roux-En-Y Gastric Bypass.

INTRODUCTION: Enhanced Recovery After Surgery (ERAS) protocols have proven to be cost-effective in various surgical procedures, mainly in colorectal surgeries. However, there is still little scientific evidence evaluating the economic impact of their application in bariatric surgery. The present study aimed to compare the economic cost of performing a laparoscopic Roux-en-Y gastric bypass following an ERAS protocol, with the costs of following a standard-of-care protocol. PATIENTS AND METHODS: A prospective non-randomized study of patients undergoing Roux-en-Y gastric bypass was performed. Patients were divided into two groups: patients following an ERAS protocol and patients following a standard-of-care protocol. The total costs of the procedure were subdivided into pharmacological expenditures, surgical material, and time expenses, the price of complementary tests performed during the hospital stay, and costs related to the hospital stay. RESULTS: The 84 patients included 58 women (69%) and 26 men (31%) with a mean age of 44.3 ± 11.6 years. There were no significant differences in age, gender, and distribution of comorbidities between groups. Postoperative pain, nausea or vomiting, and hospital stay were significantly lower within the ERAS group. The pharmacological expenditures, the price of complementary tests performed during the hospital stay, and the costs related to the hospital stay, were significantly lower in the ERAS group. There were no significant differences in the surgical material and surgical time costs between groups. Globally, the total cost of the procedure was significantly lower in the ERAS group with a mean saving of 1458.62$ per patient. The implementation of an ERAS protocol implied a mean saving of 21.25% of the total cost of the procedure. CONCLUSIONS: The implementation of an ERAS protocol significantly reduces the perioperative cost of Roux-en-Y gastric bypass.

Estimating the Impact of Influenza Vaccination on Acute and ICU Hospital Bed Usage in an Influenza Season under Endemic COVID-19 in the US.

In 2021-2022, influenza vaccine coverage in the US dropped below pre-COVID-19 pandemic levels. Cocirculation of COVID-19 and influenza could place a substantial burden on hospital utilization in future seasons, particularly given the reduced exposure to influenza during the pandemic. We used a dynamic susceptible-exposed-infected-recovered model to simulate influenza transmission with varying influenza vaccine coverage against a background of COVID-19 circulation, in order to estimate acute and ICU hospital bed occupancy for both diseases. We evaluated two vaccine scenarios: egg-based quadrivalent influenza vaccine (QIVe) for all age groups or cell-based QIV (QIVc) for 0.5-64 year-olds with adjuvanted QIV (aQIV) for ≥65 year-olds. ICU bed availability was more limiting than general hospital bed availability, with a vaccine coverage of ≥70% required to avoid negatively impacting ICU bed availability in a high-incidence influenza season. The timing of disease peaks was a key factor together with vaccine coverage, with a difference of ≥50 days needed between peak influenza and COVID-19 bed usage together with 65% influenza vaccine coverage to avoid negative impacts. QIVc + aQIV resulted in lower bed occupancy which, while not substantial, may be critical in very high hospital resource usage situations. In a situation with co-circulating influenza and COVID-19, proactive vaccination planning could help to avert overwhelming healthcare systems in upcoming influenza seasons.

A Model to Compare International Hospital Bed Numbers, including a Case Study on the Role of Indigenous People on Acute 'Occupied' Bed Demand in Australian States.

Comparing international or regional hospital bed numbers is not an easy matter, and a pragmatic method has been proposed that plots the number of beds per 1000 deaths versus the log of deaths per 1000 population. This method relies on the fact that 55% of a person's lifetime hospital bed utilization occurs in the last year of life-irrespective of the age at death. This is called the nearness to death effect. The slope and intercept of the logarithmic relationship between the two are highly correlated. This study demonstrates how lines of equivalent bed provision can be constructed based on the value of the intercept. Sweden looks to be the most bed-efficient country due to long-term investment in integrated care. The potential limitations of the method are illustrated using data from English Clinical Commissioning Groups. The main limitation is that maternity, paediatric, and mental health care do not conform to the nearness to death effect, and hence, the method mainly applies to adult acute care, especially medical and critical care bed numbers. It is also suggested that sensible comparison can only be made by comparing levels of occupied beds rather than available beds. Occupied beds measure the expressed bed demand (although often constrained by access to care issues), while available beds measure supply. The issue of bed supply is made complex by the role of hospital size on the average occupancy margin. Smaller hospitals are forced to operate at a lower average occupancy; hence, countries with many smaller hospitals such as Germany and the USA appear to have very high numbers of available beds. The so-called 85% occupancy rule is an "urban myth" and has no fundamental basis whatsoever. The very high number of "hospital" beds in Japan is simply an artefact arising from "nursing home" beds being counted as a "hospital" bed in this country. Finally, the new method is applied to the expressed demand for occupied acute beds in Australian states. Using data specific to acute care, i.e., excluding mental health and maternity, a long-standing deficit of beds was identified in Tasmania, while an unusually high level of occupied beds in the Northern Territory (NT) was revealed. The high level of demand for beds in the NT appears due to an exceptionally large population of indigenous people in this state, who are recognized to have elevated health care needs relative to non-indigenous Australians. In this respect, indigenous Australians use 3.5 times more occupied bed days per 1000 deaths (1509 versus 429 beds per 1000 deaths) and 6 times more occupied bed days per 1000 population (90 versus 15 beds per 1000 population) than their non-indigenous counterparts. The figure of 1509 beds per 1000 deaths (or 4.13 occupied beds per 1000 deaths) for indigenous Australians is indicative of a high level of "acute" nursing care in the last months of life, probably because nursing home care is not readily available due to remoteness. A lack of acute beds in the NT then results in an extremely high average bed occupancy rate with contingent efficiency and delayed access implications.