Bed demand and occupancy within the Brazilian National Health System for the most common types of cancer in Brazil, from 2018 to 2021: a cross-sectional study.

OBJECTIVE: To analyze bed demand and occupancy within the Brazilian National Health System (Sistema Único de Saúde - SUS) for the main types of cancer in Brazil, from 2018 to 2021. METHODS: This was a descriptive cross-sectional study, using data from the Hospital Information System. Queuing theory model was used for calculating average admission rate, average hospitalization rate, probability of overload, and average number of people in the queue. RESULTS: The Southeast and South regions showed the highest average hospitalization rates, while the North region showed the lowest rates. The Southeast region presented a high probability of surgical bed overload, especially in the states of São Paulo (99.0%), Minas Gerais (97.0%) and Rio de Janeiro (97.0%). São Paulo state showed an overload above 95.0% in all types of beds analyzed. CONCLUSION: There was a high probability of oncology bed occupancy within the Brazilian National Health System, especially surgical and medical beds, and regional disparities in bed overload. MAIN RESULTS: The study found a high demand for hospital admissions to oncological bed in the Southeast region and a high probability of system overload in the states of the Southeast and Northeast regions of Brazil, thus highlighting the inequities in access to healthcare services in the country. IMPLICATIONS FOR SERVICES: This study presents a methodology for the improved allocation of resources and management of surgical and medical bed flows in areas with the highest bed overload and regions with low service availability. PERSPECTIVES: It is necessary to promote public policies that ensure the equitable supply of beds for oncological treatment within the SUS, especially in states with bed overload and healthcare service gaps.

The impact of hospital saturation on non-COVID-19 hospital mortality during the pandemic in France: a national population-based cohort study.

BACKGROUND: A previous study reported significant excess mortality among non-COVID-19 patients due to disrupted surgical care caused by resource prioritization for COVID-19 cases in France. The primary objective was to investigate if a similar impact occurred for medical conditions and determine the effect of hospital saturation on non-COVID-19 hospital mortality during the first year of the pandemic in France. METHODS: We conducted a nationwide population-based cohort study including all adult patients hospitalized for non-COVID-19 acute medical conditions in France between March 1, 2020 and 31 May, 2020 (1st wave) and September 1, 2020 and December 31, 2020 (2nd wave). Hospital saturation was categorized into four levels based on weekly bed occupancy for COVID-19: no saturation (< 5%), low saturation (> 5% and ≤ 15%), moderate saturation (> 15% and ≤ 30%), and high saturation (> 30%). Multivariate generalized linear model analyzed the association between hospital saturation and mortality with adjustment for age, sex, COVID-19 wave, Charlson Comorbidity Index, case-mix, source of hospital admission, ICU admission, category of hospital and region of residence. RESULTS: A total of 2,264,871 adult patients were hospitalized for acute medical conditions. In the multivariate analysis, the hospital mortality was significantly higher in low saturated hospitals (adjusted Odds Ratio/aOR = 1.05, 95% CI [1.34-1.07], P < .001), moderate saturated hospitals (aOR = 1.12, 95% CI [1.09-1.14], P < .001), and highly saturated hospitals (aOR = 1.25, 95% CI [1.21-1.30], P < .001) compared to non-saturated hospitals. The proportion of deaths outside ICU was higher in highly saturated hospitals (87%) compared to non-, low- or moderate saturated hospitals (81-84%). The negative impact of hospital saturation on mortality was more pronounced in patients older than 65 years, those with fewer comorbidities (Charlson 1-2 and 3 vs. 0), patients with cancer, nervous and mental diseases, those admitted from home or through the emergency room (compared to transfers from other hospital wards), and those not admitted to the intensive care unit. CONCLUSIONS: Our study reveals a noteworthy "dose-effect" relationship: as hospital saturation intensifies, the non-COVID-19 hospital mortality risk also increases. These results raise concerns regarding hospitals' resilience and patient safety, underscoring the importance of identifying targeted strategies to enhance resilience for the future, particularly for high-risk patients.

Remdesivir and dexamethasone as tools to relieve hospital care systems stressed by COVID-19: A modelling study on bed resources and budget impact.

Remdesivir and dexamethasone are the only drugs providing reductions in the lengths of hospital stays for COVID-19 patients. We assessed the impacts of remdesivir on hospital-bed resources and budgets affected by the COVID-19 outbreak. A stochastic agent-based model was combined with epidemiological data available on the COVID-19 outbreak in France and data from two randomized control trials. Strategies involving treating with remdesivir only patients with low-flow oxygen and patients with low-flow and high-flow oxygen were examined. Treating all eligible low-flow oxygen patients during the entirety of the second wave would have decreased hospital-bed occupancy in conventional wards by 4% [2%; 7%] and intensive care unit (ICU)-bed occupancy by 9% [6%; 13%]. Extending remdesivir use to high-flow-oxygen patients would have amplified reductions in ICU-bed occupancy by up to 14% [18%; 11%]. A minimum remdesivir uptake of 20% was required to observe decreases in bed occupancy. Dexamethasone had effects of similar amplitude. Depending on the treatment strategy, using remdesivir would, in most cases, generate savings (up to 722€) or at least be cost neutral (an extra cost of 34€). Treating eligible patients could significantly limit the saturation of hospital capacities, particularly in ICUs. The generated savings would exceed the costs of medications.

Emprego do modelo matemático SEIHDR para auxiliar gestores na estimativa de ocupação de leitos de UTI em uma pandemia: simulação para pacientes com COVID-19 no município de Porto Alegre / Use of the SEIHDR mathematical model to assist health managers in estimating ICU bed occupancy in a pandemic: simulation for patients with COVID-19 in the city of Porto Alegre, Brazil

Introdução: A pandemia de COVID-19, no Brasil, constituiu uma ameaça ao sistema de saúde pelo risco de esgotamento dos leitos de Unidade de Terapia Intensiva (UTI). O objetivo do estudo foi projetar a ocupação de leitos de UTI com casos de COVID-19 no pico em Porto Alegre. Para isso, resolvemos utilizar uma ferramenta matemática com parâmetros da pandemia desta cidade.Métodos:Utilizamos o modelo matemático SEIHDR. Analisamos os casos de hospitalização por COVID-19 em Porto Alegre e RS até 3 de agosto de 2020 a fim de extrair os parâmetros locais para construir uma curva epidemiológica do total de casos prevalentes hospitalizados em UTI. Também analisamos as taxas de reprodução básica (R0) e reprodução efetiva (Re).Resultados: O modelo matemático projetou um pico de 344 casos prevalentes, em UTI, para o dia 22 de agosto de 2020. Calculamos 1,56 para o R0 e 1,08 no dia 3 de agosto para o Re.Conclusão: O modelo matemático simulou uma primeira onda de casos ocupando leitos de UTI muito próxima dos dados reais. Também indicou corretamente uma queda no número de casos nos dois meses subsequentes. Apesar das limitações, as estimativas do modelo matemático forneceram informações sobre as dimensões temporal e numérica de uma pandemia que poderiam ser usadas como auxílio aos gestores de saúde na tomada de decisões para a alocação de recursos frente a calamidades de saúde como o surto de COVID-19 no Brasil.

Introduction: The COVID-19 pandemic in Brazil has been a threat to health services due to the risk of bed shortage in the intensive care unit (ICU). This study aimed to estimate the bed occupancy at the ICU with patients with COVID-19 during the peak of the pandemic in Porto Alegre, capital of Rio Grande do Sul (RS), the southernmost state of Brazil. To this end, we used a mathematical model with pandemic parameters from the city.Methods: We used the SEIHDR mathematical model. We analyzed hospitalizations for COVID-19 in Porto Alegre and RS until August 3, 2020, to extract local parameters to create an epidemiological curve of the total number of prevalent cases in the ICU. We also analyzed the basic reproduction rate (R0) and effective reproduction rate (Re). Results: The mathematical model estimated a peak of 344 prevalent cases in the ICU on August 22, 2020. The model calculated an R0 of 1.56 and Re of 1.08 on August 3, 2020.Conclusion: The mathematical model accurately estimated the first peak of cases in the ICU. Also, it correctly indicated a drop in the number of cases in the following two months. Despite the limitations, the mathematical model estimates provided information on the temporal and numerical dimensions of a pandemic that could be used to assist health managers in making decisions on the allocation of resources in a state of public calamity such as the COVID-19 outbreak in Brazil.

Audit of surgical specialty patients and beds at Pietersburg Hospital, Limpopo Province, South Africa in 2021.

BACKGROUND: While the absolute number of hospital beds is usually discussed, adequate utilisation of beds is a far better instrument to measure departmental efficiency. OBJECTIVE: To measure the number of beds for each surgical specialty in Pietersburg Hospital as well as the average length of stay (LoS) to compare bed utilisation. METHOD: We conducted a 1-day descriptive cross-sectional audit of patients admitted to surgical wards on 21 April 2021 at Pietersburg Hospital. RESULTS: There were huge discrepancies in the number of beds per surgical specialty as well as the LoS. Over one-third of surgical beds were occupied by patients waiting for either a computed tomography scan, surgical procedure, or transfer. CONCLUSION: There is a need to address the functioning of the surgical specialties with regards to the number of beds allocated as well as the ideal average length of stay.

Drastic reduction of orthopaedic services at an urban tertiary hospital in South Africa during COVID-19: Lessons for the future response to the pandemic.

BACKGROUND: The COVID-19 pandemic has impacted on the global surgery landscape. OBJECTIVES: To analyse and describe the initial impact of the COVID-19 pandemic on orthopaedic surgery at Groote Schuur Hospital, a tertiary academic hospital in South Africa. METHODS: The number of orthopaedic surgical cases, emergency theatre patient waiting times, and numbers of outpatient clinic visits, ward admissions, bed occupancies and total inpatient days for January - April 2019 (pre-COVID-19) were compared with the same time frame in 2020 (COVID-19). The COVID-19 timeframe included initiation of a national 'hard lockdown' from 26 March 2020, in preparation for an increasing volume of COVID-19 cases. RESULTS: April 2020, the time of the imposed hard lockdown, was the most affected month, although the number of surgical cases had started to decrease slowly during the 3 preceding months. The total number of surgeries, outpatient visits and ward admissions decreased significantly during April 2020 (55.2%, 69.1% and 60.6%, respectively) compared with April 2019 (p<0.05). Trauma cases were reduced by 40% in April 2020. Overall emergency theatre patient waiting time was 30% lower for April 2020 compared with 2019. CONCLUSIONS: COVID-19 and the associated lockdown has heavily impacted on both orthopaedic inpatient and outpatient services. Lockdown led to a larger reduction in the orthopaedic trauma burden than in international centres, but the overall reduction in surgeries, outpatient visits and hospital admissions was less. This lesser reduction was probably due to local factors, but also to a conscious decision to avoid total collapse of our surgical services.

Estimating Brazilian states demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model

ABSTRACT BACKGROUND: The fragility of healthcare systems worldwide had not been exposed by any pandemic until now. The lack of integrated methods for bed capacity planning compromises the effectiveness of public and private hospitals' services. OBJECTIVES: To estimate the impact of the COVID-19 pandemic on the provision of intensive care unit and clinical beds for Brazilian states, using an integrated model. DESIGN AND SETTING: Experimental study applying healthcare informatics to data on COVID-19 cases from the official electronic platform of the Brazilian Ministry of Health. METHODS: A predictive model based on the historical records of Brazilian states was developed to estimate the need for hospital beds during the COVID-19 pandemic. RESULTS: The proposed model projected in advance that there was a lack of 22,771 hospital beds for Brazilian states, of which 38.95% were ICU beds, and 61.05% were clinical beds. CONCLUSIONS: The proposed approach provides valuable information to help hospital managers anticipate actions for improving healthcare system capacity.

Covid-19 no nordeste do Brasil: entre o lockdown e o relaxamento das medidas de distanciamento social / Covid-19 in the Northeast of Brazil: from lockdown to the relaxation of social distancing measures

Resumo Mesmo no período em que a pandemia de Covid-19 encontrava-se em crescimento no Nordeste do Brasil, iniciou-se a adoção de medidas de flexibilização do distanciamento social. O objetivo do estudo é o de avaliar a pertinência das propostas de flexibilização, tomando-se em conta a situação da pandemia em cada local e o momento em que foram adotadas. Tendo como referência as diretrizes da OMS, foram construídos e analisados indicadores operacionais para cada diretriz, no contexto da região Nordeste. Para análise do comportamento da epidemia, conforme indicadores selecionados, foram usadas técnicas de Joinpoint Trend Analysis, mapas de calor, razão de taxas e comparação da tendência temporal entre capitais e interior dos estados. O pico do crescimento semanal ocorreu em maio-julho/2020 (semanas epidemiológicas 19 a 31). Na maioria das capitais não se observou tendência decrescente simultânea do número de casos e óbitos nos 14 dias prévios à flexibilização. Em todos os estados o quantitativo de testes realizados foi insuficiente. Na semana epidemiológica 24 os percentuais estaduais de ocupação de leitos de UTI/Covid-19 foram próximos ou superiores 70%. A situação epidemiológica das nove capitais dos estados do Nordeste, no momento em que a decisão de flexibilização foi tomada, mostra que nenhuma delas atendia aos critérios e parâmetros recomendados pela OMS.

Abstract Even in the period when the Covid-19 pandemic was on the rise in the Northeast of Brazil, the relaxation of social distancing measures was introduced. The scope of the study is to assess, in the light of the epidemiological-sanitary situation in the region, the suitability of relaxation of social distancing measures. Based on the WHO guidelines for relaxation of social distancing, operational indicators were created and analyzed for each guideline in the context of the Northeast. To analyze the behavior of the epidemic, according to selected indicators, Joinpoint trend analysis techniques, heat maps, rate ratios and time trends between capitals and the state interior were compared. The weekly growth peak of the epidemic occurred in May-July 2020 (epidemiological weeks 19 to 31). In most capitals, there was no simultaneous downward trend in the number of cases and deaths in the 14 days prior to flexibilization. In all states the number of tests performed was insufficient. In epidemiological week 24, the state percentages of ICU/Covid-19 bed occupancy were close to or above 70%. The epidemiological situation of the nine Northeastern state capitals analyzed here did not meet criteria and parameters recommended by the World Health Organization for the relaxation of social distancing measures.

Healthcare indicators associated with COVID-19 death rates in the European Union.

OBJECTIVES: Identification of environmental and hospital indicators that may influence coronavirus disease 2019 (COVID-19) mortality in different countries is essential for better management of this infectious disease. STUDY DESIGN: Correlation analysis between healthcare system indicators and COVID-19 mortality rate in Europe. METHODS: For each country in the European Union (EU), the date of the first diagnosed case and the crude death rate for COVID-19 were retrieved from the John Hopkins University website. These data were then combined with environmental, hospital and clinical indicators extracted from the European Health Information Gateway of the World Health Organization. RESULTS: The COVID-19 death rate in EU countries (mean 1.9 ± 0.8%) was inversely associated with the number of available general hospitals, physicians and nurses. Significant positive associations were also found with the rate of acute care bed occupancy, as well as with the proportion of population who were aged older than 65 years, overweight or who had cancer. Total healthcare expenditure, public sector health expenditure and the number of hospital and acute care beds did not influence COVID-19 death rate. CONCLUSIONS: Some common healthcare system inadequacies, such as limited numbers of general hospitals, physicians and nurses, in addition to high acute care bed occupancy, may be significant drivers of nationwide COVID-19 mortality rates in EU countries.

Análisis de la demanda asistencial en la urgencia y unidad de hospitalización psiquiátrica en el contexto de pandemia por COVID-19 / Analysis of the demand for care in a psychiatric emergency room and an acute inpatient unit in the context of the COVID-19 pandemic

INTRODUCCIÓN: El objetivo consiste en analizar el impacto del COVID-19 en la demanda asistencial de las urgencias y en los ingresos psiquiátricos durante el primer mes de la pandemia. MÉTODOS: Realizamos un estudio transversal observacional retrospectivo en pacientes que acuden a urgencias psiquiátricas entre el 11 de marzo y el 11 de abril de 2019 y 2020 respectivamente. Se incluyeron variables sociodemográficas y clínicas en el estudio. Se realizaron las pruebas de Chi Cuadrado o Test exacto de Fisher para el contraste de hipótesis de variables categóricas y la prueba U Mann-Whitney para el contraste de variables cuantitativas. El nivel de significación estadística se estableció en p<0.05. Los análisis se realizaron con IBM SPSS Statistics. RESULTADOS: Se observa un descenso significativo de la media de pacientes atendidos al día en urgencias entre ambos periodos, siendo esta de 5,91 (±2,53) en 2019 y de 2,41 (±1,81) en 2020 (p<0.001). Se ha visto una disminución significativa de la ocupación media de camas en la UHB, ocupándose un 91,84% (±7,72) de camas en 2019 y un 58,85% (±13,81) en 2020 (p<0,001). En cuanto a la proporción de ingresos de los pacientes que acuden a urgencias, se ha visto un aumento significativo en el año 2020 respecto al año anterior. CONCLUSIONES: La demanda en la urgencia de pacientes psiquiátricos y la ocupación media de camas se ha reducido durante el primer mes tras la declaración de la pandemia. El miedo al contagio puede actuar como modulador de la demanda psiquiátrica.

INTRODUCTION: The aim is to analyze the impact of COVID-19 on the demand for emergency care and psychiatric admissions during the first month of the pandemic. METHODS: We conducted a retrospective, observational and cross-sectional study. We reviewed the clinical records of all patients attending the psychiatric emergency room (ER) between March 11th and April 11th, of both 2019 and 2020. Sociodemographic and clinical variables were included in the study. Chi-square test or Fisher's exact test were performed to compare categorical variables, while U Mann-Whitney U test was used for quantitative variables. The level of statistical significance was set at p<0.05. Analysis were conducted using IBM SPSS Statistics. RESULTS: The was a significant decrease in the number of patients attended in the ER. An average of 5.91 (±2.53) patients were treated per day in 2019 compared to 2.41 (±1.81) in 2020 (p<0.001). There was also a significant decrease in the occupancy rate at the inpatient psychiatric unit, with a 91.84% (±7.72) of beds occupied in 2019 and only 58.85% (±13.81) in 2020 (p<0.001). Regarding the percentage of patients admitted after assessment in the ER, there was a significant increase in 2020 compared to the previous year. CONCLUSIONS: The demand for care in the psychiatric emergency room and the average bed occupancy have decreased during the first month after the declaration of the pandemic. Fear of contagion may act as a modulator of psychiatric demand.

Does volume or occupancy influence emergency access block? A multivariate time series analysis from a single emergency department in Sydney, Australia during the COVID-19 pandemic.

OBJECTIVE: The study aims to determine whether ED presentation volume or hospital occupancy had a greater impact on ED performance before and during the COVID-19 health response at a tertiary referral hospital in Sydney, Australia. METHODS: Single centre time series analysis using routinely collected hospital and ED data from January 2019 to September 2020. The primary outcome was ED access block measured by emergency treatment performance (ETP; i.e. percentage of patients who were discharged or transferred to a ward from ED within 4 h of ED arrival time). Secondary outcomes were hospital occupancy, elective theatre cases and ambulance ramping. Multivariate time series analysis was performed using vector autoregression, to model effects of changes in various endogenous and correlated variables on ETP. RESULTS: There was an increase in ETP, drop in ED presentations and decrease in hospital occupancy between April and June 2020. Elective surgery and hospital occupancy had significant effects up to 2 days prior on ETP, while there were no significant effects of either ED or ambulance presentations on ETP. Hospital occupancy itself increased with ED presentations after 2-4 days and decreased with elective surgery after 1 day. Shocks (a one standard deviation increase) in hospital occupancy had a peak impact nearly two times greater compared to ED presentations (-1.43, 95% confidence interval -1.92, -0.93 vs -0.73, 95% confidence interval -1.21, -0.25). CONCLUSION: The main determinants of the reduction of ED overcrowding and access block during the pandemic were associated with reductions in hospital occupancy and elective surgery levels, and more research is required to assess more complex associations beyond the scope of this manuscript.

Vigilância Epidemiológica estadual no enfrentamento da pandemia pela COVID-19 no Brasil: um relato de experiência / State Epidemiological Surveillance in combating the COVID-19 pandemic in Brazil: an experience report / Vigilancia Epidemiológica estatal en el combate a la pandemia por COVID-19 en Brasil: informe de experiência

Objetivo: sistematizar a experiência do estado do Espírito Santo no enfrentamento da COVID-19, baseando-se na vivência enquanto equipe gestora e operacional da vigilância epidemiológica estadual, no período de março de 2020 a março de 2021. Método: trata-se de um estudo descritivo, do tipo relato de experiência. Os dados foram obtidos por meio de canais oficiais, alimentados por um sistema de notificação em saúde adotado pelo estado do Espírito Santo e por planilhas enviadas diariamente pelos estabelecimentos de saúde. Resultados: observou-se que a aproximação entre a gestão estadual e municipal facilitou a implementação das orientações instituídas e a consolidação das medidas em todo território capixaba, vale salientar que outros órgãos governamentais auxiliaram nesse processo. Conclusão: os desdobramentos exigidos na gestão da pandemia evidenciam a importância da Vigilância em Saúde e o papel estratégico da Vigilância Epidemiológica no controle da pandemia, e na tomada de decisão e direcionamento de recursos humanos e financeiros.

Objective: to systematize the experience of the state of Espírito Santo in facing COVID-19, based on the experience as a manager and operational team of the state epidemiological surveillance, in the period from March 2020 to March 2021. Method: this is a descriptive study, of the experience report type. The data were obtained through official channels, fed by a health notification system adopted by the State of Espírito Santo and by spreadsheets sent daily by health establishments. Results: it was observed that the approximation between state and municipal management facilitated the implementation of the instituted guidelines and the consolidation of the measures in the entire territory of the state of Espírito Santo. Conclusion: it is concluded that the developments required in the management of the pandemic highlight the importance of Health Surveillance and the strategic role of the Epidemiological Surveillance in the control of the pandemic, and in the decision making and direction of human and financial resources

Objetivo: sistematizar la experiencia de estado de Espírito Santo en el enfrentamiento del COVID-19, a partir de la experiencia como equipo gestora y operacional de la vigilancia epidemiológica estatal, de marzo de 2020 a marzo de 2021. Método: se trata de un estudio descriptivo, tipo relato de experiencia. Los datos se obtuvieron a través de canales oficiales, alimentados por un sistema de notificación sanitaria adoptado por el Estado de Espírito Santo y por planillas enviadas diariamente por los establecimientos de salud. Resultados: se observó que la aproximación entre la gestión estatal y municipal facilitó la implementación de orientaciones instituidas y la consolidación de medidas en todo el territorio del estado de Espírito Santo, cabe mencionar que otras agencias gubernamentales asistieron en este proceso. Conclusión: se concluye que los desdoblamientos exigidos en la gestión de la pandemia evidenciaron la importancia de la Vigilancia en Salud y el rol estratégico de la Vigilancia Epidemiológica en el control de la pandemia y en la toma de decisiones y direccionamiento de recursos humanos y financieros

Avaliação do tempo de desocupação e ocupação de leitos como parâmetros de governança em pacientes internados em unidade de terapia intensiva na rede pública / Evaluation of bed vacancy and occupancy times as governance parameters in patients admitted to a public intensive care unit

RESUMO Objetivo: Avaliar o tempo de desocupação e ocupação dos leitos na unidade de terapia intensiva; analisar os intervalos entre os tempos durante o período do dia e da noite, finais de semana e feriados e identificar preditores para os tempos de desocupação e ocupação. Métodos: Estudo transversal, de natureza observacional, descritivo, analítico e inferencial. Foram analisados 700 registros de desocupação-ocupação em 54 leitos na unidade de terapia intensiva adulto de um hospital da rede pública de Sergipe, entre janeiro e dezembro de 2018. O teste não paramétrico de Mann-Whitney foi utilizado para comparações entre grupos. Diversos modelos preditivos de tempo de permanência foram elaborados. A razão de taxa de incidência foi utilizada como estimativa de tamanho do efeito. Resultados: Durante o período do estudo, houve 13.477 solicitações de vaga na unidade de terapia intensiva para os 54 leitos, e apenas 5% (700 pacientes) conseguiram o acesso ao leito. Os tempos de desocupação-ocupação tiveram valores menores quando a ocupação do leito era realizada no período noturno (razão de taxa de incidência de 0,658; IC95% 0,550 - 0,787; p < 0,0001) e oferta nos finais de semana (razão de taxa de incidência de 0,566; IC95% 0,382 - 0,838; p = 0,004). O sexo feminino (razão de taxa de incidência de 0,749; IC95% 0,657 - 0,856; p < 0,0001) foi um preditor de menor tempo de desocupação-ocupação. Esse tempo tende a aumentar com a idade do paciente (razão de taxa de incidência de 1,006; IC95% 1,003 - 1,009; p < 0,0001). Conclusão: Identificaram-se disparidades no tempo de espera para a ocupação do leito, sendo maior no período diurno e em dias úteis. Mulheres e pacientes mais jovens são beneficiados por um processamento mais rápido no tempo de desocupação-ocupação.

Abstract Objective: To evaluate the vacancy and occupancy times of intensive care unit beds; to analyze differences in these times between the day and night shifts and weekdays, weekends, and holidays; and to identify predictors of vacancy and occupancy times. Methods: This was a cross-sectional, observational, descriptive, analytical, inferential study. A total of 700 vacancy-to-occupancy records from 54 beds of an adult intensive care unit of a public hospital in Sergipe, Brazil, dated between January and December 2018 were analyzed. The nonparametric Mann-Whitney test was used for comparisons between groups. Several predictive models of length of stay were constructed. The incidence rate ratio was used to estimate the effect size. Results: During the study period, there were 13,477 requests for the 54 intensive care unit beds, and only 5% (700 patients) were granted. The vacancy-to-occupancy times were shorter when beds were occupied at night (incidence rate ratio of 0.658; 95%CI 0.550 - 0.787; p < 0.0001) or on weekends (incidence rate ratio of 0.566; 95%CI 0.382 - 0.838; p = 0.004). Female sex (incidence rate ratio of 0.749; 95%CI 0.657 - 0.856; p < 0.0001) was a predictor of shorter vacancy-to-occupancy time. This time tended to increase with patient age (incidence rate ratio of 1.006; 95% CI 1.003 - 1.009; p < 0.0001). Conclusion: Disparities in the waiting time for intensive care unit beds were identified, as the time was greater in the daytime and on weekdays, and women and younger patients experienced shorter vacancy-to-occupancy times.

Principled decisions and virtuous care: an ethical assessment of the SIAARTI Guidelines for allocating intensive care resources.

This article sets forth ethical principles for responding to extraordinary circumstances in which the demand for medical care threatens to overwhelm available resources, as in the COVID-19 pandemic. In light of these principles, the author then assesses the ethics of the SIAARTI guidelines for rationing ICU beds and ventilators under such circumstances.

Guess Who's Coming to Dinner: COVID-19 in a COVID-free Unit.

OBJECTIVE: To assess the impact of the pandemic on surgical activity and the occurrence and features of Covid-19 in a Covid-free urologic unit in a regional hospital in Northern Italy. MATERIALS AND METHODS: Our Department is the only urologic service in the Trento Province, near Lombardy, the epicenter of Covid-19 in our Country. We reviewed the surgical and ward activities during the 4 weeks following the national lockdown (March 9 to April 5, 2020). The following outcomes were investigated: surgical load, rate of admissions and bed occupation, and the rate and characteristics of unrecognized Covid-positive patients. Data were compared with that of the same period of 2019 (March 11 to April 7). RESULTS AND CONCLUSION: About 63%, 70%, 64%, and 71%, decline in surgery, endoscopy, bed occupation, and admission, respectively, occurred during the 4 weeks after the lockdown, as compared to 2019. Urgent procedures also declined by 32%. Three (8%) of 39 admissions regarded unrecognized Covid-19 overlapping or misinterpreted with urgent urologic conditions such as fever-associated urinary stones or hematuria. In spite of a significant reduction of activity, a non-negligible portion of admissions to our Covid-free unit regarded unrecognized Covid-19. In order to preserve its integrity, we propose an enhanced triage prior to the admission to a Covid-free unit including not only routine questions on fever and respiratory symptoms but also nonrespiratory symptoms, history of exposure, and a survey about the social and geographic origin of the patient.

[COVID-19 Pandemic: Impact and rapid reaction of Urology]. / Pandemia COVID-19: impacto y reacción rápida de la Urología.

The COVID-19 pandemic caused by the SARS-CoV-2 virus has caused tens of thousands of deaths in Spain and has managed to breakdown the healthcare system hospitals in the Community of Madrid, largely due to its tendency to cause severe pneumonia, requiring ventilatory support. This fact has caused our center to collapse, with 130% of its beds occupied by COVID-19 patients, thus causing the absolute cessation of activity of the urology service, the practical disappearance of resident training programs, and the incorporation of a good part of the urology staff into the group of medical personnel attending these patients. In order to recover from this extraordinary level of suspended activity, we will be obliged to prioritize pathologies based on purely clinical criteria, for which tables including the relevance of each pathology within each area of urology are being proposed. Technology tools such as online training courses or surgical simulators may be convenient for the necessary reestablishment of resident education.

Multi-objective admission planning problem: a two-stage stochastic approach.

Effective admission planning can improve inpatient throughput and waiting times, resulting in better quality of service. The uncertainty in the patient arrival and the availability of resources makes the patient's allocation difficult to manage. Thus, in the admission process hospitals aim to accomplish targets of resource utilization and to lower the cost of service. Both objectives are related and in conflict. In this paper, we present a bi-objective stochastic optimization model to study the trade-off between the resource utilization and the cost of service, taking into account demand and capacity uncertainties. Real data from the surgery and medical areas of a Chilean public hospital are used to illustrate the approach. The results show that the solutions of our approach outperform the actual practice in the Chilean hospital.

Forecast UTI: aplicativo para previsão de leitos de unidades de terapia intensiva no contexto da pandemia de COVID-19 / Forecast UTI: aplicación para prever camas en Unidades de Cuidados Intensivos en el contexto de la pandemia de COVID-19 / Forecast UTI: application for predicting intensive care unit beds in the context of the COVID-19 pandemic

Frente à necessidade de gerenciamento e previsão do número de leitos de unidades de terapia intensiva (UTIs) para pacientes graves de COVID-19, foi desenvolvido o Forecast UTI, um aplicativo de livre acesso, que permite o monitoramento de indicadores hospitalares com base em dados históricos do serviço de saúde e na dinâmica temporal da epidemia por coronavírus. O Forecast UTI também possibilita realizar previsões de curto prazo do número de leitos ocupados pela doença diariamente, e estabelecer possíveis cenários de atendimento. Este artigo apresenta as funções, modo de acesso e exemplos de uso do Forecast UTI, uma ferramenta computacional destinada a auxiliar gestores de hospitais da rede pública e privada do Sistema Único de Saúde (SUS) no subsídio à tomada de decisão, de forma rápida, estratégica e eficiente.

En vista de la necesidad de administrar y prever el número de camas en la Unidad de Cuidados Intensivos para pacientes graves de COVID-19, se desarrolló Forecast UTI: una aplicación de acceso abierto que permite el monitoreo de indicadores hospitalarios basados en datos históricos del servicio salud y la dinámica temporal de esta epidemia por coronavirus También es posible hacer pronósticos a corto plazo del número de camas ocupadas diariamente por la enfermedad y establecer posibles escenarios de atención. Este artículo presenta las funciones, el modo de acceso y ejemplos de uso de Forecast UTI, una herramienta computacional capaz de ayudar a los gestores de hospitales públicos y privados en el Sistema Único de Salud, ya que apoyan la toma de decisiones de manera rápida, estratégica y eficiente.

In view of the need to manage and forecast the number of Intensive Care Unit (ICU) beds for critically ill COVID-19 patients, the Forecast UTI open access application was developed to enable hospital indicator monitoring based on past health data and the temporal dynamics of the Coronavirus epidemic. Forecast UTI also enables short-term forecasts of the number of beds occupied daily by COVID-19 patients and possible care scenarios to be established. This article presents the functions, mode of access and examples of uses of Forecast UTI, a computational tool intended to assist managers of public and private hospitals within the Brazilian National Health System by supporting quick, strategic and efficient decision-making.

Profile of general hospitals in the Unified Health System / Perfil dos hospitais gerais do Sistema Único de Saúde

ABSTRACT OBJECTIVE To characterize the organization of Brazilian general hospitals that provide services to the Unified Health System using indicators that describe the main dimensions of hospital care. METHODS A 2015 cross-sectional observational study, comprising the range of general hospitals that serve the Unified Health System. We constructed the hospital indicators from two national administrative databases: the National Registry of Health Facilities and the Hospital Information System of the Unified Health System. The indicators include the main dimensions associated with hospital care: public-private mix, production, production factors, performance, quality, case-mix and geographic coverage. Latent class analysis of indicators with bootstrapping was used to identify hospital profiles. RESULTS We identified three profiles, with hospital size being the variable with the highest degree of belonging. Small hospitals show low occupancy rates (21.36%) and high participation of hospitalizations that could have been solved with outpatient care, besides attending only medium complexity cases. They receive few non-residents, indicating that they are mainly dedicated to the local population. Medium-sized hospitals are more similar to small-sized ones: about 100% of the visits are of medium complexity, low occupancy rate (45.81%), high rate of hospitalizations for primary care sensitive conditions (17.10%) and relative importance in the healthcare provision of non-residents (26%). Large hospitals provide high complexity care, have an average occupancy rate of 64.73% and show greater geographical coverage. CONCLUSIONS The indicators point to three hospital profiles, characterized mainly by the production scale. Small hospitals show low performance, suggesting the need to reorganize hospital care provision, especially at the municipal level. The set of proposed indicators includes the main dimensions of hospital care, providing a tool that can help to plan and continuously monitor the hospital network of the Unified Health System.

RESUMO OBJETIVO Caracterizar a organização dos hospitais gerais brasileiros que prestam serviço ao Sistema Único de Saúde por meio de indicadores que descrevem as principais dimensões do cuidado hospitalar. MÉTODOS Estudo observacional transversal para o ano de 2015, compreendendo o universo dos hospitais gerais que atendem o Sistema Único de Saúde. Os indicadores hospitalares foram construídos a partir de duas bases de dados administrativos nacionais: o Cadastro Nacional de Estabelecimento de Saúde e o Sistema de Informações Hospitalares do Sistema Único de Saúde. Os indicadores contemplam as principais dimensões associadas ao cuidado hospitalar: mix público-privado, produção, fatores de produção, desempenho, qualidade, case-mix e abrangência geográfica. A análise de classes latentes dos indicadores com implementação do bootstrapping foi utilizada para a identificação dos perfis hospitalares. RESULTADOS Foram identificados três perfis, sendo porte hospitalar a variável com grau de pertencimento mais elevado. Os hospitais pequenos apresentam baixas taxas de ocupação (21,36%) e elevada participação de internações que poderiam ter sido solucionadas com cuidado ambulatorial, além de atenderem somente a média complexidade. Recebem poucos não residentes, indicando que estão dedicados praticamente à população local. Os hospitais de médio porte se assemelham mais aos de pequeno porte: cerca de 100% dos atendimentos são de média complexidade, baixa taxa de ocupação (45,81%), elevada taxa de internações por condições sensíveis à atenção primária (17,10%) e relativa importância no atendimento de não residentes (26%). Os hospitais grandes realizam os atendimentos de alta complexidade, têm taxa de ocupação média de 64,73% e apresentam maior abrangência geográfica. CONCLUSÕES Os indicadores apontam três perfis de hospitais, caracterizados principalmente pela escala de produção. Os hospitais de pequeno porte apresentam baixa performance, sugerindo a necessidade de reorganização da oferta do cuidado hospitalar, principalmente no nível municipal. O conjunto dos indicadores propostos inclui as principais dimensões do cuidado hospitalar, fornecendo uma ferramenta que pode ser utilizada no planejamento e monitoramento contínuo da rede hospitalar do Sistema Único de Saúde.