'It sort of has the feel of being at home': Mixed-methods evaluation of a pilot community-based palliative end-of-life service in a regional setting.

OBJECTIVE: To evaluate the acceptability and effectiveness of a small community-based hospice on the end-of-life experiences of patients and families. METHODS: Mixed-methods study. DESIGN: Patient admission data were used to assess utilisation of the hospice. Open-ended interviews with hospice patients and their families/carers were used to understand the emotional effects of the service. SETTING: A small palliative end-of-life hospice in a rural town in NSW, Australia, during a 12-month trial period that began in March 2019. Data were collected in October-November 2019. PARTICIPANTS: Patients, families and carers who used the hospice during the trial period, as well as staff working at the hospice. MAIN OUTCOME MEASURE(S): Quantitative measures included the number of patients admitted to the hospice, the average length of stay and the overall occupancy rate of the hospice. Quantitative interviews were used to explore the experiences of patients and families who used the hospice, and whether the hospice met their end-of-life needs. RESULTS: During the trial, 58 patients were admitted to the hospice. The majority of admissions were less than 7 days. Two patients and nine family members were interviewed about their experiences, and six staff completed interviews. Experiences were consistently positive, with the community setting of the hospice contributing to a peaceful and home-like end-of-life experience. Interviewees described meaningful relationships with staff, a pleasant physical environment and the comprehensive care provided were key elements of this experience. CONCLUSION: This model, embedding end-of-life care within a residential aged care facility, facilitated a positive end-of-life experience for residents of this regional community. The development of local models to meet local needs is essential to enabling people nearing the end of life to remain in their location of choice, and ensure that their needs are met at this vulnerable time.

Multiway p-spectral graph cuts on Grassmann manifolds.

Nonlinear reformulations of the spectral clustering method have gained a lot of recent attention due to their increased numerical benefits and their solid mathematical background. We present a novel direct multiway spectral clustering algorithm in the p-norm, for p ∈ ( 1 , 2 ] . The problem of computing multiple eigenvectors of the graph p-Laplacian, a nonlinear generalization of the standard graph Laplacian, is recasted as an unconstrained minimization problem on a Grassmann manifold. The value of p is reduced in a pseudocontinuous manner, promoting sparser solution vectors that correspond to optimal graph cuts as p approaches one. Monitoring the monotonic decrease of the balanced graph cuts guarantees that we obtain the best available solution from the p-levels considered. We demonstrate the effectiveness and accuracy of our algorithm in various artificial test-cases. Our numerical examples and comparative results with various state-of-the-art clustering methods indicate that the proposed method obtains high quality clusters both in terms of balanced graph cut metrics and in terms of the accuracy of the labelling assignment. Furthermore, we conduct studies for the classification of facial images and handwritten characters to demonstrate the applicability in real-world datasets.