scholarly journals Covid-19: Hospitals move to create extra bed capacity to relieve pressure

BMJ ◽  
2021 ◽  
pp. n2775
Author(s):  
Gareth Iacobucci
Keyword(s):  
Bed Capacity

Parameters of bed occupancy of intensive care units in Hungary

2011 ◽  
Vol 152 (24) ◽  
pp. 946-950 ◽  
Author(s):  
Miklós Gresz
Keyword(s):  
Health Care ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Health Insurance ◽  
Intensive Care Units ◽  
Emergency Care ◽  
Present Author ◽  
Bed Occupancy ◽  
National Network ◽  
Bed Capacity

According to the Semmelweis Plan for Saving Health Care, ”the capacity of the national network of intensive care units in Hungary is one but not the only bottleneck of emergency care at present”. Author shows on the basis of data reported to the health insurance that not on a single calendar day more than 75% of beds in intensive care units were occupied. There were about 15 to 20 thousand sick days which could be considered unnecessary because patients occupying these beds were discharged to their homes directly from the intensive care unit. The data indicate that on the whole bed capacity is not low, only in some institutions insufficient. Thus, in order to improve emergency care in Hungary, the rearrangement of existing beds, rather than an increase of bed capacity is needed. Orv. Hetil., 2011, 152, 946–950.

Novel indicator for the assessment of hospital bed occupancy

2011 ◽  
Vol 152 (20) ◽  
pp. 797-801 ◽  
Author(s):  
Miklós Gresz
Keyword(s):  
Patient Needs ◽  
Bed Occupancy ◽  
The Past ◽  
Hospital Beds ◽  
Hospital Bed ◽  
Bed Capacity ◽  
Statistical Indicators

In the past decades the bed occupancy of hospitals in Hungary has been calculated from the average of in-patient days and the number of beds during a given period of time. This is the only measure being currently looked at when evaluating the performance of hospitals and changing their bed capacity. The author outlines how limited is the use of this indicator and what other statistical indicators may characterize the occupancy of hospital beds. Since adjustment of capacity to patient needs becomes increasingly important, it is essential to find indicator(s) that can be easily applied in practice and can assist medical personal and funders who do not work with statistics. Author recommends the use of daily bed occupancy as a base for all these statistical indicators. Orv. Hetil., 2011, 152, 797–801.

scholarly journals COVID-19 in conflict border regions: a case of South Kordofan, Sudan

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Quraish Sserwanja ◽  
Mohammed Bashir Adam ◽  
Joseph Kawuki ◽  
Emmanuel Olal
Keyword(s):  
Case Fatality ◽  
Mechanical Ventilators ◽  
Governmental Organizations ◽  
Non Governmental Organizations ◽  
Bed Capacity ◽  
Displaced People ◽  
Set Up ◽  
One Year ◽  
Novel Coronavirus ◽  
South Kordofan

AbstractThe novel coronavirus disease (COVID-19) was first reported in Sudan on 13 March 2020. Since then, Sudan has experienced one of the highest rates of COVID-19 spread and fatalities in Africa. One year later, as per 22 March 2021, Sudan had registered 29,661 confirmed cases and 2,028 deaths with a case fatality rate (CFR) of 6.8 %. By 12 December 2020, of the 18 states in Sudan, South Kordofan had the fifth highest CFR of 17.4 %, only surpassed by the other conflict affected North (57.5 %), Central (50.0 %) and East (31.8 %) Darfur States. By late March 2021, just three months from December 2020, the number of cases in South Kordofan increased by 100 %, but with a significant decline in the CFR from 17.4 to 8.5 %. South Kordofan is home to over 200,000 poor and displaced people from years of destructive civil unrests. To date, several localities such as the Nubba mountains region remain under rebel control and are not accessible. South Kordofan State Ministry of Health in collaboration with the federal government and non-governmental organizations set up four isolation centres with 40 total bed capacity, but with only two mechanical ventilators and no testing centre. There is still need for further multi-sectoral coalition and equitable allocation of resources to strengthen the health systems of rural and conflict affected regions. This article aims at providing insight into the current state of COVID-19 in South Kordofan amidst the second wave to address the dearth of COVID-19 information in rural and conflict affected regions.

scholarly journals Optimal Control for a COVID-19 Model Accounting for Symptomatic and Asymptomatic

2020 ◽  
Vol 8 (1) ◽  
pp. 168-179
Author(s):  
Jead M. Macalisang ◽  
Mark L. Caay ◽  
Jayrold P. Arcede ◽  
Randy L. Caga-anan
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Medical Care ◽  
Optimal Control Theory ◽  
Comparable Result ◽  
Type Model ◽  
Hospital Beds ◽  
Transmission Reduction ◽  
Bed Capacity ◽  
The Government

AbstractBuilding on an SEIR-type model of COVID-19 where the infecteds are further divided into symptomatic and asymptomatic, a system incorporating the various possible interventions is formulated. Interventions, also referred to as controls, include transmission reduction (e.g., lockdown, social distancing, barrier gestures); testing/isolation on the exposed, symptomatic and asymptomatic compartments; and medical controls such as enhancing patients’ medical care and increasing bed capacity. By considering the government’s capacity, the best strategies for implementing the controls were obtained using optimal control theory. Results show that, if all the controls are to be used, the more able the government is, the more it should implement transmission reduction, testing, and enhancing patients’ medical care without increasing hospital beds. However, if the government finds it very difficult to implement the controls for economic reasons, the best approach is to increase the hospital beds. Moreover, among the testing/isolation controls, testing/isolation in the exposed compartment is the least needed when there is significant transmission reduction control. Surprisingly, when there is no transmission reduction control, testing/isolation in the exposed should be optimal. Testing/isolation in the exposed could seemingly replace the transmission reduction control to yield a comparable result to that when the transmission reduction control is being implemented.

Nowcasting for improved management of COVID-19 acute bed capacity

2021 ◽  
pp. 1-3
Author(s):  
Richard M Wood
Keyword(s):  
Strategic Planning ◽  
Healthcare Services ◽  
Bed Occupancy ◽  
Bed Capacity ◽  
Occupancy Rates ◽  
Second Wave ◽  
Bed Occupancy Rates

As the second wave of COVID-19 continues to push healthcare services to their limits, rapid and strategic planning has never been more important. Richard M Wood explains how statistical ‘nowcasting’ can be used to predict bed occupancy rates and help leaders to better manage acute capacity during this ongoing crisis.

scholarly journals Impact of COVID‐19 on acute isolation bed capacity and nursing workforce requirements: A retrospective review

2021 ◽  
Author(s):  
Esther Monica Peijin Fan ◽  
Ngoc Hoang Long Nguyen ◽  
Shin Yuh Ang ◽  
Fazila Aloweni ◽  
Hui Qi Ivy Goh ◽  
...  
Keyword(s):  
Retrospective Review ◽  
Nursing Workforce ◽  
Bed Capacity

scholarly journals Changes in the Number of Intensive Care Unit Beds in U.S. Hospitals During the Early Months of the COVID-19 Pandemic, as reported to the National Healthcare Safety Network’s COVID-19 Module

2021 ◽  
pp. 1-12
Author(s):  
Lindsey M. Weiner-Lastinger ◽  
Margaret A. Dudeck ◽  
Katherine Allen-Bridson ◽  
Raymund Dantes ◽  
Cindy Gross ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Type ◽  
National Healthcare ◽  
National Healthcare Safety Network ◽  
Bed Capacity ◽  
Using Data

Abstract Using data from the National Healthcare Safety Network (NHSN), we assessed changes to intensive care unit (ICU) bed capacity during the early months of the COVID-19 pandemic. Changes in capacity varied by hospital type and size. ICU beds increased by 36%, highlighting the pressure placed on hospitals during the pandemic.

scholarly journals Interregional Transfers for Pandemic Surges

2020 ◽  
Author(s):  
Kenneth A Michelson ◽  
Chris A Rees ◽  
Jayshree Sarathy ◽  
Paige VonAchen ◽  
Michael Wornow ◽  
...  
Keyword(s):  
The United States ◽  
Upper Bounds ◽  
Hospital Inpatient ◽  
Worst Case ◽  
Icu Patients ◽  
Interregional Transfers ◽  
Number Of Patients ◽  
Bed Capacity ◽  
Model Scenarios ◽  
Do So

Abstract Background Hospital inpatient and intensive care unit (ICU) bed shortfalls may arise due to regional surges in volume. We sought to determine how interregional transfers could alleviate bed shortfalls during a pandemic. Methods We used estimates of past and projected inpatient and ICU cases of coronavirus disease 2019 (COVID-19) from 4 February 2020 to 1 October 2020. For regions with bed shortfalls (where the number of patients exceeded bed capacity), transfers to the nearest region with unused beds were simulated using an algorithm that minimized total interregional transfer distances across the United States. Model scenarios used a range of predicted COVID-19 volumes (lower, mean, and upper bounds) and non–COVID-19 volumes (20%, 50%, or 80% of baseline hospital volumes). Scenarios were created for each day of data, and worst-case scenarios were created treating all regions’ peak volumes as simultaneous. Mean per-patient transfer distances were calculated by scenario. Results For the worst-case scenarios, national bed shortfalls ranged from 669 to 58 562 inpatient beds and 3208 to 31 190 ICU beds, depending on model volume parameters. Mean transfer distances to alleviate daily bed shortfalls ranged from 23 to 352 miles for inpatient and 28 to 423 miles for ICU patients, depending on volume. Under all worst-case scenarios except the highest-volume ICU scenario, interregional transfers could fully resolve bed shortfalls. To do so, mean transfer distances would be 24 to 405 miles for inpatients and 73 to 476 miles for ICU patients. Conclusions Interregional transfers could mitigate regional bed shortfalls during pandemic hospital surges.

scholarly journals How Many Hospital Beds?

2002 ◽  
Vol 39 (4) ◽  
pp. 400-412 ◽  
Author(s):  
Linda V. Green
Keyword(s):  
New York ◽  
New York State ◽  
Bed Occupancy ◽  
Capacity Decisions ◽  
Timely Fashion ◽  
Bed Capacity ◽  
The Common ◽  
Primary Measure ◽  
Operational Data ◽  
Average Occupancy

For many years, average bed occupancy level has been the primary measure that has guided hospital bed capacity decisions at both policy and managerial levels. Even now, the common wisdom that there is an excess of beds nationally has been based on a federal target of 85% occupancy that was developed about 25 years ago. This paper examines data from New York state and uses queueing analysis to estimate bed unavailability in intensive care units (ICUs) and obstetrics units. Using various patient delay standards, units that appear to have insufficient capacity are identified. The results indicate that as many as 40% of all obstetrics units and 90% of ICUs have insufficient capacity to provide an appropriate bed when needed. This contrasts sharply with what would be deduced using standard average occupancy targets. Furthermore, given the model's assumptions, these estimates are likely to be conservative. These findings illustrate that if service quality is deemed important, hospitals need to plan capacity based on standards that reflect the ability to place patients in appropriate beds in a timely fashion rather than on target occupancy levels. Doing so will require the collection and analysis of operational data—such as demands for and use of beds, and patient delays—which generally are not available.

scholarly journals 47 COVID-19 Impact on Burn Care- A Summary of Weekly Bed Counts and Surge Capacity

2021 ◽  
Vol 42 (Supplement_1) ◽  
pp. S35-S35
Author(s):  
Jeffrey E Carter ◽  
Herbert Phelan ◽  
Colleen M Ryan ◽  
James C Jeng ◽  
Kathryn Mai ◽  
...  
Keyword(s):  
Substantial Reduction ◽  
Surge Capacity ◽  
Burn Centers ◽  
Resource Limitations ◽  
Burn Care ◽  
Regional Trends ◽  
Number Of Patients ◽  
Bed Capacity ◽  
Initial Survey ◽  
The Impact

Abstract Introduction The COVID-19 pandemic has raised global awareness of healthcare resource limitations. Specifically, the pandemic has demonstrated that burn disaster planning should involve non-burn disasters that threaten staff, supplies, or space. The ABA facilitated bed counts with the assistance of regional disaster coordinators from April through August of 2020. Our analysis examines the impact of the pandemic on burn surge and bed capacity in the U.S. Methods Bed availability was obtained by the ABA regional disaster coordinators through an initiative by the Organization and Delivery of Burn Care Committee. Bed availability was defined as immediately available burn beds and categorized as adult, pediatric, or flexible. Surge capacity was defined as the maximum number of patients that a burn center could admit in a surge situation. Data was deidentified by the central office with descriptive statistics to determine bed availability and surge capacity trends regionally and nationally. Results Bed counts were performed 6 times from 04/17/2020 through 08/14/2020. Response rates from the 137 North American burn centers varied from 86–96%. At least 6 burn centers (5%) were either closed or converted for COVID patients during the initial two bed counts. The total number of adult or pediatric burn beds was 2,082. Total bed availability decreased from 845 at the first survey down to 572 beds at the last survey. Surge capacity baseline was 1,668 beds and decreased from 1,132 beds in the initial survey down to 833 beds in the final survey. Conclusions Our study demonstrates a significant impact on burn bed availability due to the COVID-19 pandemic with a 37% reduction in available burn beds from April to August and a 26% reduction in surge capacity. This study demonstrates a substantial reduction in bed availability during the pandemic with additional analysis in process to examine regional trends.

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