Care Beds (care + bed)

Distribution by Scientific Domains

Selected Abstracts

Impact of the post-World War II generation on intensive care needs in Norway

Background: A high birth rate during the first two decades following World War II has increased the proportion of elderly people in present-day society and, consequently, the demand for health-care services. The impact on intensive care services may become dramatic because the age distribution of critically ill patients is skewed towards the elderly. We have used registry data and population statistics to forecast the demand for intensive care services in Norway up until the year 2025. Methods: Data collected by the Norwegian intensive care registry (NIR), showing the age distribution in Norwegian intensive care units (ICU) during the years 2006 and 2007, were used with three different Norwegian prognostic models of population growth for the years 2008,2025 to compute the expected increase in intensive care unit bed-days (ICU bed-days). Results: The elderly were overrepresented in Norwegian ICUs in 2006,2007, with patients from 60 to 79 years of age occupying 44% of ICU bed-days. Population growth from 2008 to 2025 was estimated to be from 11.1 to 26.4%, depending on the model used. Growth will be much larger in the age group 60,79 years. Other factors kept unchanged, this will result in an increase in the need for intensive care (ICU bed-days) of between 26.1 and 36.9%. Conclusion: The demand for intensive care beds will increase markedly in Norwegian hospitals in the near future. This will have serious implications for the planning of infrastructure, education of health care personnel, as well as financing of our health care system. [source]

Nurse-led discharge from high dependency unit

Gillian Knight
Summary ,High dependency care is a rapidly evolving area of critical care, with high patient turnover, which ultimately leads to high levels of pressure for beds ,There is a growing trend emerging, recognizing the importance and value of nurse-led initiatives in delivering effective nursing care in acute care settings ,One specific nurse-led initiative this author has developed is that of nurse-led discharge (NLD) from the high dependency unit (HDU), in order to optimize the utilization of critical care beds within the HDU ,An audit of the current practice was undertaken, which ultimately led to the implementation of NLD ,Early experiences indicate that HDU beds are now being used more effectively [source]

An observational cohort study of triage for critical care provision during pandemic influenza: ,clipboard physicians' or ,evidenced based medicine'?

ANAESTHESIA, Issue 11 2009
T. Guest
Summary We assessed the impact of a United Kingdom government-recommended triage process, designed to guide the decision to admit patients to intensive care during an influenza pandemic, on patients in a teaching hospital intensive care unit. We found that applying the triage criteria to a current case-mix would result in 116 of the 255 patients (46%) admitted during the study period being denied intensive care treatment they would have otherwise received, of which 45 (39%) survived to hospital discharge. In turn, 69% of those categorised as too ill to warrant admission according to the criteria survived. The sensitivity and specificity of the triage category at ICU admission predicting mortality was 0.29 and 0.84, respectively. If the need for intensive care beds is estimated to be 275 patients per week, the triage criteria would not exclude enough patients to prevent the need for further rationing. We conclude that the proposed triage tool failed adequately to prioritise patients who would benefit from intensive care. [source]

Modelling the impact of an influenza A/H1N1 pandemic on critical care demand from early pathogenicity data: the case for sentinel reporting

ANAESTHESIA, Issue 9 2009
A. Ercole
Summary Projected critical care demand for pandemic influenza H1N1 in England was estimated in this study. The effect of varying hospital admission rates under statistical uncertainty was examined. Early in a pandemic, uncertainty in epidemiological parameters leads to a wide range of credible scenarios, with projected demand ranging from insignificant to overwhelming. However, even small changes to input assumptions make the major incident scenario increasingly likely. Before any cases are admitted to hospital, 95% confidence limit on admission rates led to a range in predicted peak critical care bed occupancy of between 0% and 37% of total critical care bed capacity, half of these cases requiring ventilatory support. For hospital admission rates above 0.25%, critical care bed availability would be exceeded. Further, only 10% of critical care beds in England are in specialist paediatric units, but best estimates suggest that 30% of patients requiring critical care will be children. Paediatric intensive care facilities are likely to be quickly exhausted and suggest that older children should be managed in adult critical care units to allow resource optimisation. Crucially this study highlights the need for sentinel reporting and real-time modelling to guide rational decision making. [source]

Emergency Department Patient Flow: The Influence of Hospital Census Variables on Emergency Department Length of Stay

Ray Lucas MD
Abstract Objectives:, The objective was to evaluate the association between hospital census variables and emergency department (ED) length of stay (LOS). This may give insights into future strategies to relieve ED crowding. Methods:, This multicenter cohort study captured ED LOS and disposition for all ED patients in five hospitals during five 1-week study periods. A stepwise multiple regression analysis was used to examine associations between ED LOS and various hospital census parameters. Results:, Data were analyzed on 27,325 patients on 161 study days. A significant positive relationship was demonstrated between median ED LOS and intensive care unit (ICU) census, cardiac telemetry census, and the percentage of ED patients admitted each day. There was no relationship in this cohort between ED LOS and ED volume, total hospital occupancy rate, or the number of scheduled cardiac or surgical procedures. Conclusions:, In multiple hospital settings, ED LOS is correlated with the number of admissions and census of the higher acuity nursing units, more so than the number of ED patients each day, particularly in larger hospitals with busier EDs. Streamlining ED admissions and improving availability of inpatient critical care beds may reduce ED LOS. [source]

Estimating Observation Unit Profitability with Options Modeling

Christopher W. Baugh MD
Abstract Background:, Over the past two decades, the use of observation units to treat such common conditions as chest pain, asthma, and others has greatly increased. These units allow patients to be directed out of emergency department (ED) acute care beds while potentially avoiding inpatient admission. Many studies have demonstrated the clinical effectiveness of care delivered in such a setting compared to the ED or inpatient ward. However, there are limited data published about observation unit finance. Methods:, Using the economic principles of stock options, opportunity costs, and net present value (NPV), a model that captures the value generated by admitting a patient to an observation unit was derived. In addition, an appendix is included showing how this model can be used to calculate the dollar value of an observation unit admission. Results:, A model is presented that captures more complexity of observation finance than the simple difference between payments and costs. The calculated estimate in the Appendix suggests that the average value of a single observation unit admission was about $2,908, which is about 40% higher than expected. Conclusion:, Subtraction of costs from payments may significantly underestimate the financial value of an observation unit admission. However, the positive value generated by an observation unit bed must be considered in the context of other projects available to hospital administrators. [source]