scholarly journals Hospital outreach service: Helping to prevent nursing home placement

1998 ◽  
Vol 21 (4) ◽  
pp. 192 ◽  
Author(s):  
Phillip Bairstow ◽  
Sarah Ashe ◽  
Mary Bairstow
Keyword(s):  
Nursing Home ◽  
Length Of Stay ◽  
Health Service ◽  
Hospital Length ◽  
Nursing Home Placement ◽  
Hospital Length Of Stay ◽  
Advantages And Disadvantages ◽  
Outreach Service ◽  
Home Placement

An outreach service from a post-acute metropolitan teaching hospital delivered anintensive, multidisciplinary and coordinated allied health service, and achieved bothearly hospital discharge and the prevention or delay of nursing home placement. Thisarticle reports on three types of cases which illustrate how the service assisted wardteams, families and patients to determine whether nursing home placement wasessential. For a group of 20 cases, the total reduction in hospital length of stay was556 days, and home accommodation as an alternative to nursing homeaccommodation was achieved for a total of 7505 days. The article outlines a matrixof advantages and disadvantages, both tangible and intangible, of home versusnursing home accommodation. It is suggested that a full costing of this matrix wouldinform debate on the comparative merits of long-term home and nursing homeaccommodation.

scholarly journals Time between Symptom Onset, Hospitalisation and Recovery or Death: a Statistical Analysis of Different Time-Delay Distributions in Belgian COVID-19 Patients

2020 ◽  
Author(s):  
Christel Faes ◽  
Steven Abrams ◽  
Dominique Van Beckhoven ◽  
Geert Meyfroidt ◽  
Erika Vlieghe ◽  
...  
Keyword(s):  
Nursing Home ◽  
Length Of Stay ◽  
Symptom Onset ◽  
Age Groups ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Age Group ◽  
Median Length ◽  
Nursing Home Patients ◽  
Interval Censored

Background There are different patterns in the COVID-19 outbreak in the general population and amongst nursing home patients. Different age-groups are also impacted differently. However, it remains unclear whether the time from symptom onset to diagnosis and hospitalization or the length of stay in the hospital is different for different age groups, gender, residence place or whether it is time dependent. Methods Sciensano, the Belgian Scientific Institute of Public Health, collected information on hospitalized patients with COVID-19 hospital admissions from 114 participating hospitals in Belgium. Between March 14, 2020 and June 12, 2020, a total of 14,618 COVID-19 patients were registered. The time of symptom onset, time of COVID-19 diagnosis, time of hospitalization, time of recovery or death, and length of stay in intensive care are recorded. The distributions of these different event times for different age groups are estimated accounting for interval censoring and right truncation in the observed data. Results The truncated and interval-censored Weibull regression model is the best model for the time between symptom onset and diagnosis/hospitalization best, whereas the length of stay in hospital is best described by a truncated and interval-censored lognormal regression model. Conclusions The time between symptom onset and hospitalization and between symptom onset and diagnosis are very similar, with median length between symptom onset and hospitalization ranging between 3 and 10.4 days, depending on the age of the patient and whether or not the patient lives in a nursing home. Patients coming from a nursing home facility have a slightly prolonged time between symptom onset and hospitalization (i.e., 2 days). The longest delay time is observed in the age group 20-60 years old. The time from symptom onset to diagnosis follows the same trend, but on average is one day longer as compared to the time to hospitalization. The median length of stay in hospital varies between 3 and 10.4 days, with the length of stay increasing with age. However, a difference is observed between patients that recover and patients that die. While the hospital length of stay for patients that recover increases with age, we observe the longest time between hospitalization and death in the age group 20-60. And, while the hospital length of stay for patients that recover is shorter for patients living in a nursing home, the time from hospitalization to death is longer for these patients. But, over the course of the first wave, the length of stay has decreased, with a decrease in median length of stay of around 2 days.

The effect of context on performance of an acute medical unit: experience from an Australian tertiary hospital

2012 ◽  
Vol 36 (3) ◽  
pp. 320 ◽  
Author(s):  
Belinda Suthers ◽  
Robert Pickles ◽  
Michael Boyle ◽  
Kichu Nair ◽  
Justyn Cook ◽  
...  
Keyword(s):  
Emergency Department ◽  
Nursing Home ◽  
Length Of Stay ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Local Context ◽  
Health Staff ◽  
Medical Unit ◽  
Acute Medical Unit ◽  
Transfers Of Care

Objective. To ascertain the improvements in length of stay and discharge rates following the opening of an acute medical unit (AMU). Methods. Retrospective cohort study of all patients admitted under general medicine from June–November 2008. Main outcome measures were length of stay in hospital and in the emergency department (ED). Results. The length of time spent in the emergency department for those admitted to the AMU was significantly shorter than those admitted directly to a medical ward (6.83 h v. 9.40 h, P < 0.0001). A trend towards shorter hospital length of stay continued after the AMU opened compared with the same period in the previous year (5.15 days (2.49, 11.57 CI) v. 5.66 days (2.76, 11.52 CI)). However, the number of ward transfers for a patient and the need to wait for a nursing home bed or public rehabilitation affected length of stay much more than the AMU. Conclusion. An AMU was successful in decreasing ED length of stay and contributed to decreasing hospital length of stay. However, we suggest that local context is crucially important in tailoring an AMU to obtain maximal benefit, and that AMUs are not a ‘one size fits all’ solution. What is known about the topic? Acute Medical Units were pioneered in the UK and have been shown to decrease length of stay with no increase in adverse events. As a result, they have been enthusiastically adopted in Australia. However, most studies have been single point ‘before/after’ designs looking at all medical patients, and there has been little consideration of the context in which AMUs operate and how this might affect their performance. What does this paper add? We consider length of stay trends over many years and separate single organ disease from multi-system disease patients, in order to ensure that gains are not simply a result of selective entry of healthier patients into AMUs. We also show that the effect of an AMU is small compared with other systemic issues, such as waiting for nursing home placement and the number of transfers of care. What are the implications for practitioners? Although there may be gains in terms of length of stay in the emergency department, those considering the establishment of an AMU need to consider other factors that may mitigate the improvements in hospital length of stay, such as the roadblocks to discharge, the organisation of allied health staff, and the number of transfers of care.

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