Exploring various models of hospice care worldwide that can be used and adapted to the context of Qatar: A review of the literature
Bibliographic record
Abstract
Background: Hospice care is an alternative for those patients who wish to die at home. Most clients who have a terminal illness would rather choose the services provided by healthcare workers who deliver hospice care in the client’s home. For some, it is important to have the ability to spend time with friends, family and to die with dignity and respect at their preferable place of death. Qatar has established end of life care services for patients with advanced stages of cancer, however these services are delivered on palliative care units housed within the National Center for Cancer Care and Research (NCCCR). Having the ability to provide at home hospice care is a necessity in order to carry out the wish of clients who wish to die at home, fulfil the gap in these facilities, and achieve the goal of Qatar’s national health strategy, which is to improve cancer services.Aim: To explore the literature for different models of at-home hospice care worldwide then find a model that can be adapted to the context of Qatar.Methods: A literature review approach was used. Nine scholarly articles were found that focused on and evaluated different at-home hospice models of care worldwide published between 2007 and 2018. Articles were critically appraised using the Mixed Method Appraisal Tool. The data were analysed by categorizing the included articles in a spreadsheet based on study design.Results: The most significant components of at-home models of hospice care were multidimensional care, staff competent in delivering end of life care services, and the ability to provide twenty-four-hour care in the home. These components had a positive impact on providing safe effective end of life care services at home.Conclusions: Taken together, all the necessary components identified in this literature review will go a long way in the successful development of hospice care in Qatar.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".