BackgroundPatients in acute care hospitals no longer in need of acute care are called Alternate Level of Care (ALC) patients. This is growing and common all across Canada. A better understanding of this patient population would help to address this problem.MethodsA chart review was conducted in two hospitals in New Brunswick. All patients designated as ALC on July 1, 2009 had their charts reviewed.ResultsThirty-three per cent of the hospital beds were occupied with ALC patients; 63% had a diagnosis of dementia. The mean length of stay was 379.6 days. Eighty-six per cent were awaiting a long-term care bed in the community. Most patients experienced functional decline during their hospitalization. One year prior to admission, 61% had not been admitted to hospital and 59.2% had had at least one visit to the emergency room.ConclusionsThe majority of the ALC patients in hospital have a diagnosis of dementia and have been waiting in hospital for over one year for a long-term care bed in the community. Many participants were recipients of maximum home care in the community, suggesting home maker services alone may not be adequate for some community-dwelling older adults. Early diagnosis of dementia, coupled with appropriate care in the community, may help to curtail the number of patients with dementia who end up in hospital as ALC patients.

Introduction: Much of the research and policy reports on Alternate Level of Care (ALC) in Canada have focused on the impact ALC has on acute care services. To date, the experiences and opinions of those who must wait in hospital for alternate services have been largely absent from discussions. Method: A qualitative study was conducted with patients and families designated as ALC in one urban and two rural hospitals in Atlantic Canada. Data were analyzed using content analysis. Results: Three themes emerged from the data: a perception of normalcy, being old but not sick and anticipating relocation to another facility.

Quantitative fatty acid signature analysis (QFASA) is a recent diet estimation method that depends on statistical techniques. QFASA has been used successfully to estimate the diet of predators such as seals and seabirds. Given the potential species in the predator's diet, QFASA uses statistical methods to obtain point estimates of the proportion of each species in the diet. In this paper, inference for a population of predators is considered.The estimated diet is compositional and often with zeros corresponding to species that are estimated to be absent from the diet. Zeros of this type (referred to as essential zeros) are troublesome since typical methods of dealing with compositional data involve logarithmic transformations. In this paper, we develop mixture models that can be used to model compositional data with essential zeros. We then present inference procedures for the true diet of a predator that are based on the developed models and designed for the difficult but practical setting in which sample sizes are small. Simulations using "pseudo-seals" are carried out to assess the fit of our models and our confidence intervals. Two real-life data sets involving seabirds and seals illustrate the usefulness of our confidence interval methods in practice. Supplemental materials for this article are available online.

Compositional data are met in many different fields, such as economics, archaeometry, ecology, geology and political sciences. Regression where the dependent variable is a composition is usually carried out via a log-ratio transformation of the composition or via the Dirichlet distribution. However, when there are zero values in the data these two ways are not readily applicable. Suggestions for this problem exist, but most of them rely on substituting the zero values. In this paper we adjust the Dirichlet distribution when covariates are present, in order to allow for zero values to be present in the data, without modifying any values. To do so, we modify the log-likelihood of the Dirichlet distribution to account for zero values. Examples and simulation studies exhibit the performance of the zero adjusted Dirichlet regression.

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