ICU Beds Research Articles

Risk of death among patients hospitalized with COVID-19 in Mato Grosso during the first year of the pandemic, Brazil

Objective: To analyze the factors associated with hospital mortality due to COVID-19 in Mato Grosso in 2020. Methods: We considered the hospitalization records from March to December 2020, from patients with COVID-19 aged 19 years or older residing in Mato Grosso. Data were obtained from the state government’s system and Hazard Ratios were estimated using the Poisson regression model. Results: Of the 17,523 hospitalization records of COVID-19, 4,147 died (23.7%), with higher risk of death among patients aged 40 years or older, black-brown, indigenous, some comorbidity, who were admitted to the ICU bed, who did not reside in the central macro-region of the state, and who were hospitalized in June and July, those with the highest concentration of hospitalizations for COVID-19. Conclusion: Besides the individual factors, organization and preparation of the care network to attend to severe cases of the disease were associated with risk of death by COVID-19.

Feasible intervention combinations for achieving a safe exit of the Zero-COVID policy in China and its determinants: an individual-based model study

BackgroundAlthough several pathways have been proposed as the prerequisite for a safe phase-out in China, it is not clear which of them are the most important for keeping the mortality rate low, what thresholds should be achieved for these most important interventions, and how the thresholds change with the assumed key epidemiological parameters and population characteristics.MethodsWe developed an individual-based model (IBM) to simulate the transmission of the Omicron variant in the synthetic population, accounting for the age-dependent probabilities of severe clinical outcomes, waning vaccine-induced immunity, increased mortality rates when hospitals are overburdened, and reduced transmission when self-isolated at home after testing positive. We applied machine learning algorithms on the simulation outputs to examine the importance of each intervention parameter and the feasible intervention parameter combinations for safe exits, which is defined as having mortality rates lower than that of influenza in China (14.3 per 100, 000 persons).ResultsWe identified vaccine coverage in those above 70 years old, number of ICU beds per capita, and the availability of antiviral treatment as the most important interventions for safe exits across all studied locations, although the thresholds required for safe exits vary remarkably with the assumed vaccine effectiveness, as well as the age structure, age-specific vaccine coverage, community healthcare capacity of the studied locations.ConclusionsThe analytical framework developed here can provide the basis for further policy decisions that incorporate considerations about economic costs and societal impacts. Achieving safe exits from the Zero-COVID policy is possible, but challenging for China’s cities. When planning for safe exits, local realities such as the age structure and current age-specific vaccine coverage must be taken into consideration.

0291 Attending Physician Perceptions of Nightshift Work in the ICU: Results from a Large Tertiary Medical Center

Abstract Introduction Nightshifts represent a substantial proportion of time dedicated to working in the inpatient setting, particularly among ICU staff. Our institution implemented a 24/7 in-person ICU attending model more than a decade ago. With practice growth and more than 200 ICU beds across disciplines, there are now at least 8 ICU attendings in-hospital all night. Yet, little is known about attending staff perceptions and desires about night work, so we began an exploratory analysis. Methods An online survey of 13 multiple-choice, slider scale, and open-ended questions were sent via email to critical care staff physicians of different disciplines within our institution. Results 69 out of 150 physicians completed the survey (46% response rate). Half were between 35 and 45 years old; 29% were age 45 to 55 years old. About half self-identified as a morningness chronotype. Most (84%) work 3- or 4-night shifts consecutively. Most viewed night shift work as having a negative influence on their quality of life (48% “somewhat negative” and 22% “very negative”) and on their health (51% “somewhat negative” and 24% “very negative”). Most would choose to work less nightshifts (37%) or none (29%). During nightshift assignments, about half (53%) self-report an average of 5 hours of sleep per 24-hour period; 18% self-report ≤ 4hours. Only 6% reported 7 or 8 hours of sleep. Mitigating strategies utilized during series of night shifts include use of caffeine (78%), naps (66%) and use of sleeping aids (21%). Outside of the nightshift series, more than half (56%) reported no sleep difficulties while 21% reported onset or maintenance insomnia. Conclusion At our large tertiary hospital employing an in-house nightshift model across multiple ICUs, most staff ICU physicians have a negative perception of night shift work on their quality of life and health. The majority of respondents would choose to work less or no night shifts. How self-reports of limited sleep (average 5 hours) per 24-hour period compare to objectively measured sleep duration in this population remains to be determined in the next phase of this study. Support (if any)

Chronic noncommunicable diseases aggravate hospitalizations and deaths from covid-19

The objective of this study was to analyze the association of non-communicable chronic diseases (NCDs) with cases of hospitalizations and deaths due to covid-19. It is a cross-sectional, analytical study, with a quantitative approach of secondary data, collected in the Influenza Epidemiological Surveillance Information System, linked to the Ministry of Health - Brazil. The variable “covid-19” was selected from the database, along with sociodemographic information (gender, race/color, age group and education) and clinical information (comorbidities, type of ventilatory support used, ICU bed stay, case evolution for death or cure), of patients with reported cases of Severe Acute Respiratory Syndrome (SARS) in the year 2020, in the city of Campo Grande/MS. 5152 notifications of SARS due to covid-19 were identified, accounting for 60.6% of hospitalizations in the year 2020 and, of these, 64.2% associated with comorbidities. Kidney diseases were the ones that presented the highest relative risk for the need for hospitalization in an ICU bed and evolution to death. The presence of comorbidities, represented mostly by CNCDs, were related to the greater severity of hospitalizations due to covid-19.

744 Characteristics of Verified and Designated Burn Centers

Abstract Introduction Burn centers serve an essential role in providing specialized care for the injured. Professional societies (verify) and state agencies (designate) these facilities through a process that evaluates the resources, processes, and capabilities of each burn center. Over 90% of the level 1 or 2 trauma centers in the US and only around 50% of burn centers are verified. The goal of our study was to evaluate the variability of verified and designated burn centers and trauma centers in the US. Methods The Databases for Optimal Resources for Injury Care (DORIC) is a centralized database developed by the American Hospital Association, American College of Surgeons Committee on Trauma, American Burn Association, all fifty US states’ Departments of Health, and claims databases through a collaboration with BData, LSUHSC, Spectral MD, and UNO. Categorical data was assessed using Fisher’s exact while continuous variables were assessed with paired t-test and confidence intervals. The analysis included hospital and burn ICU bed count, hospital revenue, ED visits, discharges, and urban vs rural geography. Results The database includes 134 burn centers of which 75 were verified (56%), 91% were in an urban setting and 87% were co-located with a trauma center. Hospitals had a median of 492 staffed beds, 79,449 ER visits, and 18,437 discharges. Burn centers had a median of 11 burn ICU beds and 3,285 hospital days/year. Urban vs rural geography was not different between verified and designated burn centers (p=0.54). All categories of revenue were associated with burn center verification. Conclusions Our study demonstrates no significant difference with the hospital size, location (urban vs rural), ER volume, hospital beds, or burn ICU beds. Significant differences were identified with the rate of discharge and revenues which could be attributed to services, quality, or reimbursement. Given that only half of burn care occurs at verified burn centers, additional research is needed to better understand these significant differences. Applicability of Research to Practice A keen understanding of burn center characteristics is essential to serve the burn professionals that work at burn centers and the communities they serve.

Use the ARIMA and EMG Models to Predict the Confirmed Cases and ICU Bed Occupancy Data of COVID-19 in Massachusetts and Compare the Accuracy of the Two Models

Beginning in 2019, COVID-19 has invaded our lives and continues until now. People are still being effort made to control the spread of the virus and treat patients. Two variables in COVID-19 data are confirmed data and ICU bed occupancy data. Collect the data, use the ARIMA model and EMG model to predict the data, and then compare it with the actual data. Through comparison, it is found that there is a small gap between the ARIMA predicted value and the actual data, which can be used to predict the data of these two variables. In the process of fighting against COVID-19, it is very important to strengthen medical service capabilities, adequate treatment resources, and strengthen the construction of ICU wards. The construction of ICU is very complicated and involves many medical equipment, including ventilator, infusion pump, electrocardiogram machine, extracorporeal membrane oxygenation machine (ECMO), oximeter and so on. Therefore, the accuracy of data prediction is very important. Sufficient ICU beds and medical resources can be prepared according to the forecast. Do a good job of safeguarding the treatment work and medical services to ensure the level and quality of patient treatment and avoid causing panic.

Management of the COVID-19 pandemic in Rhineland-Palatinate hospitals of all levels of care : Results of the COVID-19 Registry RLP.

The COVID-19 pandemic placed asignificant burden on the German healthcare system. Based on the experience of severe disease progression of the SARS-CoV‑2 infection from neighboring European countries in the early 2020s, with ICU overload and high mortality rates, efforts were made in Germany to increase the capacity of available ICU beds. Subsequently, all documentation and reporting focused on the ICU capacities for COVID-19patients. It was hypothesized that mainly afew large hospitals provided care for the majority of COVID-19patients. The COVID-19 Registry RLP of Rhineland-Palatinate documented SARS-CoV‑2 inpatients from daily mandatory queries of all hospitals throughout the pandemic from April 2020 to March 2023, distinguishing between patients in ICUs and normal wards. In its 18thCorona Ordinance, the state government required all hospitals to participate in the care of SARS-CoV‑2 inpatients. We investigated the participation of hospitals at different levels of care in Rhineland-Palatinate in the management of the COVID-19 pandemic. Nine pandemic waves were documented during the pandemic and exemplary data on the respective pandemic peaks were evaluated. Adistinction was made between the burden on hospitals at different levels of care: primary care hospitals, standard care hospitals, specialty hospitals, and maximal care hospitals. Analysis of the data showed that all hospital types participated equally in the care of SARS-CoV-2patients. The requirement of the Ministry of Health of Rhineland-Palatinate to provide at least 20% of the available capacity was met by all levels of care and there were no disparities between hospitals of different levels of care in the management of the pandemic.Hospitals at all levels of care participated equally in the care of SARS-CoV‑2 inpatients and thus contributed significantly to the management of the pandemic in Rhineland-Palatinate.

Relationships among hospital acute ischemic stroke volumes, hospital characteristics, and outcomes in the US

Background and ObjectivesPrior research on volume-based patient outcomes related to acute ischemic stroke (AIS) have demonstrated contradictory results and fail to reflect recent advances in stroke care. We sought to examine contemporary relationships between hospital AIS volumes and outcomes. MethodsWe used complete Medicare datasets in a retrospective cohort study using validated International Classification of Diseases Tenth Revision codes to identify patients admitted with AIS from January 1, 2016 through December 31, 2019. AIS volume was calculated as the total number of AIS admissions per hospital during the study period. We examined several hospital characteristics by AIS volume quartile. We performed adjusted logistic regressions testing associations of AIS volume quartiles with: inpatient mortality, receipt of tissue plasminogen activator (tPA) and endovascular therapy (ET), discharge home, and 30-day outpatient visit. We adjusted for sex, age, Charlson comorbidity score, teaching hospital status, MDI, hospital urban-rural designation, stroke certification status and ICU and neurologist availability at the hospital. ResultsThere were 952400 AIS admissions among 5084 US hospitals; AIS 4-year volume quartiles were: 1st: 1-8 AIS admissions; 2nd: 9-44; 3rd: 45-237; 4th: 238+. Highest quartile hospitals more often were stroke-certified (49.1% vs 8.7% in lowest quartile, p<0.0001), with ICU bed availability (19.8% vs 4.1%, p<0.0001) and with neurologist expertise (91.1% vs 3%, p<0.0001). In the highest AIS quartile (compared to the lowest quartile), there was lower inpatient mortality (odds ratio [OR] 0.71 [95%CI 0.57-0.87, p<0.0001]), lower 30-day mortality (0.55 [0.49-0.62], p<0.0001), greater receipt of tPA (6.60 [3.19-13.65], p<0.0001) and ET (16.43 [10.64-25.37], p<0.0001, and greater likelihood of discharge home (1.38 [1.22-1.56], p<0.0001). However, when the highest quartile hospitals were examined separately, higher volumes were associated with higher mortality despite higher rates of tPA and ET receipt. ConclusionsHigh AIS-volume hospitals have greater utilization of acute stroke interventions, stroke certification and availability of neurologist and ICU care. These features likely play a role in the better outcomes observed at such centers, including inpatient and 30-day mortality and discharge home. However, the highest volume centers had higher mortality despite greater receipt of interventions. Further research is needed to better understand volume-outcome relationships in AIS to improve care at lower volume centers.

Tracheostomy Patient Care Unit. An innovative Otorhinolaryngology solution of a transversal nature for the hospital

Background and objectiveThe care of tracheostomized patients are high risk skills and low incidence. Strategies for improvement of health care in hospital wards and specialties other than otolaryngology based solely on training have not been able to offer an adequate solution. A tracheostomized patient unit is presented directed by the otolaryngology service to attend all tracheostomized hospitalised patients of all specialties. Material and methodsBackground: Third level public hospital with 876 hospitalisation beds and 30 ICU beds for 481,296 inhabitants. Unit model: Transversal unit for the hospital providing attention to all tracheostomized patients, adults, and children, of all specialties, with dedication of 50% of a ENT nurse of hospitalisation that moves to the hospitalisation bed of the specialty of each patient and 50% of another office ENT nurse for ambulatory patients care, with the consultancy of an ENT specialist and coordinated by the ENT supervisor. Results572 patients between 2016 and 2021, 80% men, aged 63 ± 14 years, were attended in the Unit. 14.7 ± 2 tracheostomized patients daily and 96 ± 4 complication annual consultations were attended, rising up to 19 tracheostomized patients daily by 2020 and 141 ± 8.4 consultations by complications in 2020 and 2021, during the COVID-19 pandemic. The mean stay of the non-ENT specialties was reduced in 13 days, increasing the satisfaction of the ENT and non-ENT professionals and the satisfaction of the users. ConclusionsA Tracheostomized Patient Care Unit proactively directed from the Otorhinolaryngology Service to transversally care for all tracheostomized patients improves the quality of health care by reducing stay, complications, and emergencies. Improves the satisfaction of non-otolaryngological professionals by reducing the anxiety of facing care of patients who lack knowledge and experience and that of ENT specialists and nurses by reducing unplanned extemporaneous demands for care. Improves user satisfaction by perceiving adequate continuity of care. The Otorhinolaryngology Services provide their experience in the management of laryngectomized and tracheostomized patients and in teamwork with other specialists and professionals without the need to create new structures outside Otorhinolaryngology.

What Is Going on in Indoor Air Quality of a University Hospital in Northern Cyprus?

There are two main purposes of microbial monitoring of the inanimate hospital environment. One of them is to monitor hygiene standards, and the second is to determine the presence of nosocomial pathogens. This study was aimed to investigate the indoor environment of the different departments of a university hospital. The prospective study was conducted in a university hospital, a teaching hospital with 143 beds and 30 ICU beds, and a hospital with 6 different wards in Northern Cyprus. Active air sampling was done by using an air IDEAL 3P device. Air samples were taken at 38 points defined before in different parts of the hospital. Our results showed a low level of microorganisms' numbers in microbial airborne communities in a university hospital. Moreover, our results indicated that the temperature of the hospital's indoor environment is not significantly related to the airborne microbial community. On the other hand, our results indicate that the Aspergillus species were mostly isolated in the drug preparation room. The studies have shown that one of the causes of hospital infections is the microorganisms entering the airborne microbial communities. In this case, epidemiology and pathogenesis of airborne microbial communities should be understood.

Association Between Levels of Intensive Care and In-Hospital Mortality in Patients Hospitalized for Sepsis Stratified by Sequential Organ Failure Assessment Scores.

To assess the association between levels of intensive care and in-hospital mortality in patients hospitalized for sepsis, stratified by Sequential Organ Failure Assessment (SOFA) score at admission. A nationwide, propensity score-matched, retrospective cohort study. A Japanese national inpatient database with data on 70-75% of all ICU and high-dependency care unit (HDU) beds in Japan. Adult patients hospitalized for sepsis with SOFA scores greater than or equal to 2 on their day of admission between April 1, 2018, and March 31, 2021, were recruited. Propensity score matching was performed to compare in-hospital mortality, and patients were stratified into 10 groups according to SOFA scores. Two exposure and control groups according to treatment unit on day of admission: 1) ICU + HDU versus general ward and 2) ICU versus HDU. Of 97,070 patients, 19,770 (20.4%), 23,066 (23.8%), and 54,234 (55.9%) were treated in ICU, HDU, and general ward, respectively. After propensity score matching, the ICU + HDU group had significantly lower in-hospital mortality than the general ward group, among cohorts with SOFA scores greater than or equal to 6. There were no significant differences in in-hospital mortality among cohorts with SOFA scores 3-5. The ICU + HDU group had significantly higher in-hospital mortality than the general ward among cohorts with SOFA scores of 2. The ICU group had lower in-hospital mortality than the HDU group among cohorts with SOFA scores greater than or equal to 12. There were no significant differences in in-hospital mortality among cohorts with SOFA scores 5-11. The ICU group had significantly higher in-hospital mortality than the general ward group among cohorts with SOFA scores less than or equal to 4. Patients hospitalized for sepsis with SOFA scores greater than or equal to 6 in the ICU or HDU had lower in-hospital mortality than those in the general ward, as did those with SOFA scores greater than or equal to 12 in the ICU versus HDU.

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

BackgroundIn 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. MethodsThe 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. ResultsThe 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. ConclusionsThe 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.

Relationships among Hospital Acute Ischemic Stroke Volumes, Hospital Characteristics, and Outcomes in the US (P14-5.025)

<h3>Objective:</h3> We sought to examine contemporary relationships between hospital acute ischemic stroke (AIS) volumes and outcomes. <h3>Background:</h3> Prior research on AIS volume-based patient outcomes demonstrated contradictory results and failed to reflect recent advances in stroke care. <h3>Design/Methods:</h3> We used complete Medicare datasets in a retrospective cohort study employing validated International Classification of Diseases Tenth Revision codes to identify patients admitted with AIS from January 1, 2016 through December 31, 2019. AIS volume was calculated as the total number of AIS admissions per hospital during the study period. We examined hospital characteristics by AIS volume quartile. We performed adjusted logistic regression testing associations of AIS volume with: inpatient mortality, receipt of tissue plasminogen activator (tPA) and endovascular therapy (ET), discharge home and 30-day outpatient visit. We adjusted for sex, age, Charlson comorbidity score, teaching hospital status, socioeconomic status, hospital urban-rural designation, stroke certification status, and ICU and neurologist availability at the hospital. <h3>Results:</h3> There were 952400 AIS admissions among 5084 US hospitals; AIS 4-year volume quartiles were: 1st: 1–8 AIS admissions; 2nd: 9–44; 3rd: 45–237; 4th: 238+. Highest quartile hospitals more often were stroke-certified (49.1% vs 8.7% in lowest quartile, p&lt;0.0001), with ICU bed availability (19.8% vs 4.1%, p&lt;0.0001) and with neurologist expertise (91.1% vs 3%, p&lt;0.0001). For every ten-unit increase in volume, there were higher odds of receiving tPA (OR 1.009, 95% CI 1.008–1.01, p&lt;0.0001) and ET (1.041, 1.037–1.046, p&lt;0.0001), but also higher inpatient mortality (1.004, 1.003–1.005, p&lt;0.0001) and 30-day mortality (1.001, 1.001–1.002, p&lt;0.0001). <h3>Conclusions:</h3> High AIS-volume hospitals have greater utilization of acute stroke interventions, stroke certification and availability of neurologist and ICU care. Despite these advantages, higher AIS volumes were associated with increased inpatient and 30-day mortality. Further research is needed to better understand volume-outcome relationships in AIS to provide effective stroke care and accurately risk-adjust hospital outcomes. <b>Disclosure:</b> Dr. McCarthy has nothing to disclose. Dr. Daniel has nothing to disclose. Dr. Santos has nothing to disclose. Dr. Dhamoon has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for Faegre Baker Daniels LLP. Dr. Dhamoon has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for Wellstar Health System Inc. Dr. Dhamoon has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for Fabiani Cohen &amp; Hall, LLP. Dr. Dhamoon has received personal compensation in the range of $5,000-$9,999 for serving as an Expert Witness for Kramer, Dillof, Livingston &amp; Moore. Dr. Dhamoon has received personal compensation in the range of $500-$4,999 for serving as an Expert Witness for Robins Kaplan. Dr. Dhamoon has received personal compensation in the range of $5,000-$9,999 for serving as an Expert Witness for Parker Waichman LLP. Dr. Dhamoon has received personal compensation in the range of $500-$4,999 for serving as an Expert Witness for Heidell, Pittoni, Murphy &amp; Bach, LLP.

Automated APACHE II and SOFA score calculation using real-world electronic medical record data in a single center.

The integration of illness severity and organ dysfunction scores into clinical practice, including the APACHE II and SOFA scores, has been challenging due to constraints associated to manual score calculation. With electronic medical records (EMR), score calculation automation using data extraction scripts has emerged as a solution. We aimed to demonstrate that APACHE II and SOFA scores calculated with an automated EMR-based data extraction script predict important clinical endpoints. In this retrospective cohort study, every adult patient admitted to one of our three ICUs, between July 1, 2019, and December 31, 2020, were enrolled. For every patient, an automated ICU admission APACHE II score was calculated using EMR data and minimal clinician input. Fully automated daily SOFA scores were calculated for every patient. 4 794 ICU admissions met our selection criteria. Of these ICU admissions, 522 deaths were recorded (10.9% in-hospital mortality rate). The automated APACHE II was discriminant for in-hospital mortality (AU-ROC = 0.83 (95% CI 0.81-0.85)). We observed an association between the APACHE II score and ICU LOS, with a statistically significant mean increase of 1.1days of ICU LOS (1.1 [1-1.2]; p = < .0001) for each 10 units increase in APACHE score. SOFA score curves did not discrimate significantly between survivors and non-survivors. A partially automated APACHE II score, calculated with real-world EMR data using an extraction script, is associated with in-hospital mortality risk. The automated APACHE II score could potentially constitute an acceptable surrogate of ICU acuity to be used in resource allocation and triaging, especially in time of high demand for ICU beds.

Health and Economic Impacts of Lockdown Policies in the Early Stage of COVID-19 in the United States

Lockdown policies, such as stay-at-home orders, are known to be effective in controlling the spread of the novel coronavirus disease 2019. However, concerns over economic burdens of these policies rapidly propelled U.S. states to move toward reopening in the early stage of the pandemic. Decision making in most states has been challenging, especially because of a dearth of quantitative evidence on health gains versus economic burdens of different policies. To assist decision makers, we study the health and economic impacts of various lockdown policies across U.S. states and shed light on policies that are most effective. To this end, we make use of detailed data from 50 U.S. states plus the District of Columbia on various factors, including number of tests, positive and negative results, hospitalizations, ICU beds and ventilators used, residents’ mobility obtained from cellphone data, and deaths. Our analyses allow quantifying the total cost versus the total quality-adjusted life year (QALY) associated with various lockdown policies. We utilize a compartmental model with Markov chain Monte Carlo simulation to estimate the spread of disease. To calibrate our model separately for each U.S. state, we make use of empirical data on the intensity of intervention policies, age, ratio of Black/Hispanic populations, per capita income, residents’ mobility, and number of daily tests and feed them to a longitudinal mixed-effect model. Finally, we utilize a microsimulation model to estimate the total cost and total QALY for each state and perform cost-effectiveness analysis to identify policies that would have worked best. Our results show that, compared with no intervention during March–June 2020, the policies undertaken across the United States saved, on average, about 41,284.51 years’ worth of QALY (per 100K capita), incurring $164.01 million (per 100K capita). Had the states undertaken more strict policies during the same time frame than those they adopted, these values would be 44,909.41 years and $117.28 million, respectively. By quantifying the impact of various lockdown policies separately for each state, our results allow federal and state authorities to avoid following a “one size fits all” strategy and instead enact policies that are better suited for each state. Specifically, by studying the trade-offs between health gains and economic impacts, we identify the particular states that would have benefited from implementing more restrictive policies. Finally, in addition to shedding light on the impact of lockdown policies during our study period (March–June 2020), our results have important implications on curbing future fast-spreading variants of the coronavirus or other related potential epidemics.Supplemental Material: The online appendix is available at https://doi.org/10.1287/serv.2023.0321 .

COVID-19 Vaccination and Healthcare Demand

One of the driving concerns during any epidemic is the strain on the healthcare system. As we have seen many times over the globe with the COVID-19 pandemic, hospitals and ICUs can quickly become overwhelmed by cases. While strict periods of public health mitigation have certainly helped decrease incidence and thus healthcare demand, vaccination is the only clear long-term solution. In this paper, we develop a two-module model to forecast the effects of relaxation of non-pharmaceutical intervention and vaccine uptake on daily incidence, and the cascade effects on healthcare demand. The first module is a simple epidemiological model which incorporates non-pharmaceutical intervention, the relaxation of such measures and vaccination campaigns to predict caseloads into the Fall of 2021. This module is then fed into a healthcare module which can forecast the number of doctor visits, the number of occupied hospital beds, number of occupied ICU beds and any excess demand of these. From this module, we can also estimate the length of stay of individuals in ICU. For model verification and forecasting, we use the four most populous Canadian provinces as a case study.

Assessing the surge capacity of hospitals in Ugandan health care systems in managing the COVID-19 pandemic

IntroductionThe increasing cases of COVID-19 poses a threat on the over strained health care systems, especially in developing countries. Health care systems might need a surge to accommodate the ever increasing number of COVID1-19 cases. Hence, we assessed the Ugandan healthcare systems’ capacity to accommodate the surge in the increased caseloads, which might need admission and critical care due to COVID-19.ObjectivesUnderstanding the health systems capacity to accomadate the surge in increase caseload of COVID-19MethodsWe assumed that 2% of the Uganda population get symptomatic infections by COVID-19 based on modelled estimates of Uganda and ascertained the healthcare systems surge capacity for COVID-19 under three transmission curves scenarios; 6, 12 and 18 months. We estimated four measures for hospital surge capacity; ICU bed surge capacity, ICU bed tipping point, hospital bed capacity and hospital bed tipping point. Estimates were made for national level and 132 district local government.ResultsThe capacity of Ugandan health care system to accommodate the increasing numbers of cases due to COVID-19 is hindered by the lack of oxygen. Only 9 in 20 (46%) of hospital beds had oxygen supply. The hospital bed surge capacity varied across districts. Under the 12 months transmission scenario, the proportion of hospital with available beds, that would accommodate COVID-19 cases varied from 4% in Karomoja district, to 84% in Kampala district. The Ugandan healthcare systems faces a critical gap in ICU beds and ventilator capacity. Only 48 out of 132 districts had at least 1 ICU unit. An additional 2,247 bed and 2,756 ventilators (12 months transmission curve) will be needed to accommodate the caseloads due to COVID-19.ConclusionsThe capacity for Ugandan healthcare systems to manage to manage the COVID-19 caseloads is minimal. There need to address the sub-national variations in bed surge capacity, ICU units and ventilators within the Ugandan healthcare system.Disclosure of InterestNone Declared

Fila única de leitos e a pandemia de COVID-19: atuação do Poder Legislativo Federal no ano de 2020

Abstract This study investigated legislative proposals on the single waiting list for hospitalizations and ICU beds within the scope of the Federal Legislative Branch in the first year of the pandemic (2020). This was an exploratory, qualitative, and document- based study, which analyzed bills analyzed in the Brazilian National Congress on the subject. The results were organized according to the authors’ profile and qualitative content of the bills. There was a predominance of male parliamentarians, affiliated with left-wing parties and professional training in areas other than health. Most bills dealt with a general single waiting list, specifying hospital beds, the mixed management of hospital beds, and indemnity through the Brazilian Unified Health System’s (SUS, in Portuguese) price table. The House of Representatives presented more bills, but no progress was made in their processing. Among the analyzed bills, only one was prioritized in the External Commission to Combat COVID-19. It was concluded that the Federal Legislative Branch once again missed the chance to legislate for the future and prepare the country with a normative framework capable of confronting health emergencies, which will demand much from health managers and SUS itself.

Single waiting list for hospital beds during the COVID-19 pandemic: performance of the Federal Legislative Branch in 2020.

This study investigated legislative proposals on the single waiting list for hospitalizations and ICU beds within the scope of the Federal Legislative Branch in the first year of the pandemic (2020). This was an exploratory, qualitative, and document- based study, which analyzed bills analyzed in the Brazilian National Congress on the subject. The results were organized according to the authors' profile and qualitative content of the bills. There was a predominance of male parliamentarians, affiliated with left-wing parties and professional training in areas other than health. Most bills dealt with a general single waiting list, specifying hospital beds, the mixed management of hospital beds, and indemnity through the Brazilian Unified Health System's (SUS, in Portuguese) price table. The House of Representatives presented more bills, but no progress was made in their processing. Among the analyzed bills, only one was prioritized in the External Commission to Combat COVID-19. It was concluded that the Federal Legislative Branch once again missed the chance to legislate for the future and prepare the country with a normative framework capable of confronting health emergencies, which will demand much from health managers and SUS itself.

Relationship between intensive care surge capacity and hospital factors: an extensive experience.

As a prolonged surge scenario, the COVID-19 pandemic has offered an unparalleled opportunity to improve hospital surge capacity (SC) understanding and the ability to manage it. In this study, the authors report the experience of a large hospital network and evaluate potential relationships between Intensive Care Units SC (ICU-SC) and some hospital-related variables: bed occupancy, emergency department admissions, ward admission from ED, and elective surgery procedures. Pearson's partial correlation coefficient (r) has been used to define the relationship between SC and the daily values of the above variables, collected through a dedicated digital platform that also ensured a regular quality check of the data. The observation has concerned several levels of analysis, namely two different types of SC calculation (SC base-SCb and SC actual-SCa), hospital category level and multi-hospital level, and two consecutive pandemic waves. Among the 16 hospitals observed, the correlation was shown to be moderate-positive with non-ICU bed occupancy (r/ = 0.62, r/ = 0.54), strong/moderate with ICU bed occupancy (r/ = 0.72, r/ = 0.54), and moderate with ward admissions from ED (r/ = 0.50, r/ = 0.51) On the contrary, the correlation proved to be moderate-negative with ED admissions (r/ = - 0.69, r/ = - 0.62) and low with the number of elective surgery procedures (r/ = - 0.10, r/ = - 0.16). This study identified a positive correlation between SC and three variables monitored: ICU bed occupancy, non-ICU bed occupancy, and ward admissions from ED. On the contrary, the correlation was negative for ED admission and the number of elective surgery procedures. The results have been confirmed across all levels of analysis adopted.