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Record W2048629623 · doi:10.4103/0973-1075.150170

Impact of specialist home-based palliative care services in a tertiary oncology set up: A prospective non-randomized observational study

2015· article· en· W2048629623 on OpenAlexaboutno aff
SunilR Dhiliwal, Maryann Muckaden

Bibliographic record

VenueIndian Journal of Palliative Care · 2015
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePalliative careReferralPsychosocialObservational studyDistressQuality of life (healthcare)Family medicineNursingPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Home-based specialist palliative care services are developed to meet the needs of the patients in advanced stage of cancer at home with physical symptoms and distress. Specialist home care services are intended to improve symptom control and quality of life, enable patients to stay at home, and avoid unnecessary hospital admission. MATERIALS AND METHODS: Total 690 new cases registered under home-based palliative care service in the year 2012 were prospectively studied to assess the impact of specialist home-based services using Edmonton symptom assessment scale (ESAS) and other parameters. RESULTS: Out of the 690 registered cases, 506 patients received home-based palliative care. 50.98% patients were cared for at home, 28.85% patients needed hospice referral and 20.15% patients needed brief period of hospitalization. All patients receiving specialist home care had good relief of physical symptoms (P < 0.005). 83.2% patients received out of hours care (OOH) through liaising with local general practitioners; 42.68% received home based bereavement care and 91.66% had good bereavement outcomes. CONCLUSION: Specialist home-based palliative care improved symptom control, health-related communication and psychosocial support. It promoted increased number of home-based death, appropriate and early hospice referral, and averted needless hospitalization. It improved bereavement outcomes, and caregiver satisfaction.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.161
GPT teacher head0.465
Teacher spread0.303 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations37
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueIndian Journal of Palliative CareSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207