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Consensus development: Within general oncology practice, what constitutes high-quality palliative care delivery?

2013· article· en· W2591301926 on OpenAlexaff
Kathleen Bickel, Kristen K. McNiff, Jennifer L. Malin, Amy Pickar Abernethy, Anupama Kurup Acheson, Charles L. Shapiro, Tracey L. Evans, Arif H. Kamal, Mary K. Buss, Dale Lupu, Michael S. Broder, Monika K. Krzyzanowska

Bibliographic record

VenueJournal of Clinical Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsCancer Care Ontario
Fundersnot available
KeywordsMedicinePalliative carePsychosocialDelphi methodReferralScope (computer science)Scale (ratio)Scope of practiceNursingMultidisciplinary approachFamily medicineQuality of life (healthcare)OncologyHealth care

Abstract

fetched live from OpenAlex

280 Background: Multiple studies illustrate the benefits of combined palliative and standard cancer care, but oncology practices need guidance to fill existing gaps in delivering high quality palliative care (PC) to cancer patients. As a first step, ASCO and the American Academy of Hospice and Palliative Medicine (AAHPM) sought to develop a consensus definition of which PC aspects are within the purview of general adult oncology practice in the United States. Methods: An ASCO and AAHPM steering group used existing publications to define 9 domains of PC in oncology: Symptom Assessment and Management (A&M), Psychosocial A&M, Spiritual and Cultural A&M, Communication and Shared Decision-Making, Care Planning, Appropriate Palliative Care and Hospice Referral, Coordination and Continuity of Care, Carer Support, and End-of-Life Care. Within each domain, key PC activities were itemized and described (e.g. pain assessment using a standardized scale at every clinical encounter), totaling 966 activities. A 31-member multidisciplinary panel participated in a modified RAND Delphi process, rating each activity on a 9-point scale according to 3 constructs: importance, feasibility, and scope of practice. Composite scoring categorized activities as either reasonably within scope of oncology practice, uncertain, or typically not in scope. Results: The response rate for each round was 94%. Notable panelist concerns included the breadth of palliative care practice, the varied access that oncology practices have to PC resources, and the varied individual knowledge and comfort with specific activities. Despite multiple small ranking changes between surveys, only 41 activities changed in scope of practice category. Of 966 activities, 62% were ranked as reasonably within scope of oncology practice, 36% were uncertain, and 2% were typically not in scope. Conclusions: Despite the diverse range of PC activities, panelists strongly agreed that more than half were reasonably within the scope of adult medical oncology practice. These items provide a foundation for improving palliative care delivery within an oncology practice, with suggestions for future performance measures and quality improvement activities.

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)0.291
metaresearch head score (Gemma)0.455
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.291
Threshold uncertainty score0.875

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2910.455
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0090.009
Science and technology studies0.0050.012
Scholarly communication0.0120.012
Open science0.0060.017
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.420
GPT teacher head0.585
Teacher spread0.165 · 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.

Study designQualitative
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

Citations1
Published2013
Admission routes1
Has abstractyes

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