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Record W1966844927 · doi:10.1111/jocn.12704

Commentary on Jack B, Baldry C, Groves K, Whelan A, Sephton J and Gaunt K (2013) Supporting home care for the dying: an evaluation of healthcare professionals’ perspectives of an individually tailored hospice at home service. Journal of Clinical Nursing 22, 2778–2786

2015· letter· en· W1966844927 on OpenAlexaboutno aff
Claudia Virdun, Jane Phillips

Bibliographic record

VenueJournal of Clinical Nursing · 2015
Typeletter
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPalliative careNursingHealth careMedicineService (business)Intervention (counseling)PopulationPsychologyBusiness

Abstract

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A combination of population ageing and increasing complexity of care, combined with the need to deliver cost-effective treatments, is driving the development and evaluation of novel models of palliative care (Evans et al. 2013). The article by Jack et al. (2013) adopts a mixed methods evaluation to explore the perceptions of community-based clinicians about an expanded home-based service for patients with palliative care needs that includes: (1) an accompanied transfer home process (2) a medically led multi-disciplinary specialist palliative care crisis intervention service; and (3) in home hospice aides (composed of registered nurses and care assistants). What is evident from the evaluation is that this additional layer of practical support increased the capacity of the existing healthcare team to deliver care that was responsive to the patient and their care givers’ unique needs. It also appears to better support people living alone who wish to remain at home. While this evaluation is limited to the perceptions of health professionals, it suggests that the addition of these extra care elements enables more people to remain at home for longer. Although this evaluation focuses almost exclusively on processes of care and the outcome of place of death (home setting or other), rather than explicitly reporting on the quality of end of life care, it is important work that provides us with insights into the feasibility of potential strategies that enable people to remain at home for longer. These findings concur with evidence from a recent rapid review of models of palliative care which identified a number of important elements of care including: (1) access to specialist palliative care knowledge and expertise; (2) case management, coordination and promotion of communication across care settings; (3) providing support for home-based care including after-hours access; (4) tailoring and targeting services to the target population and setting, particularly when addressing cultural needs; (5) considering workforce issues across the care continuum; (6) collaboration across the healthcare continuum including home, community, acute and residential aged care; and (7) better integrating health and social services to support palliative care in the community (Luckett et al. 2014). While the lack of patient and care-giver reported outcomes or perspectives is an acknowledged limitation of the work by Jack et al. (2013), it is important that future studies better utilise relevant patient reported palliative care outcome measures (Antunes et al. 2014). Steinhauser et al. (2000) noted over a decade ago that dying at home was considered least important by patients nearing the end of life, with this finding confirmed more recently by another large Canadian study (Heyland et al. 2006), suggesting that dying at home may not necessarily be the most appropriate proxy measure for service quality. Integrating patient and family measures of importance, patient reported outcome measures, service delivery processes and cost analyses to develop and implement optimal models of care for those requiring palliative care is an important next step. The authors have confirmed that all authors meet the ICMJE criteria for authorship credit (www.icmje.org/ethical_1author.html), as follows: (1) substantial contributions to conception and design of, or acquisition of data or analysis and interpretation of data, (2) drafting the article or revising it critically for important intellectual content, and (3) final approval of the version to be published.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.066
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.067
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.002
Science and technology studies0.0050.006
Scholarly communication0.0040.005
Open science0.0080.003
Research integrity0.0470.060
Insufficient payload (model declined to judge)0.0120.014

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.

Opus teacher head0.251
GPT teacher head0.555
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations2
Published2015
Admission routes1
Has abstractyes

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