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The PaCES (Palliative Care Early and Systematic) Project: Impact of individual components of a multi-faceted intervention on early referral to specialist palliative care.

2022· article· en· W4298139203 on OpenAlexaffabout
Aynharan Sinnarajah, Madalene A. Earp, Patricia Biondo, Camille Piquette, Janet Vandale, Patricia A. Tang, Marc Kerba, Sharon Watanabe, Amy Tan, Jessica Simon

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsAlberta Health ServicesUniversity of Calgary
Fundersnot available
KeywordsMedicineReferralPalliative careClinical nurse specialistIntervention (counseling)Family medicineNursing

Abstract

fetched live from OpenAlex

199 Background: Early referral to specialist palliative care can improve, or maintain, symptom and quality of life outcomes that matter most to patients facing life-limiting illnesses. We tested a multifaceted oncologist-facing intervention (Palliative Care Early and Systematic) in the real-world setting of a busy outpatient cancer clinic for its ability to increase the proportion of patients who receive early specialist palliative care (defined as ≥ 90 days before death). Herein, we describe how each component of the multi-faceted intervention, intended to bridge cancer, primary, and palliative care, impacted early use of specialist palliative care among advanced colorectal cancer patients. Methods: Two intervention components were implemented in Calgary, Alberta, Canada’s tertiary cancer centre from January 2019 to June 2020: 1) Adult colorectal cancer patients were referred to a community-based Clinical Nurse Specialist if they failed, or could not receive, first-line chemotherapy, or had high symptom burden (indicated by an Edmonton Symptom Assessment System Revised score ≥ 7); 2) Medical oncologists sent templated ‘Shared Care’ letters to patients’ primary care providers to improve communication, collaboration and role clarity. Results: N = 209 eligible patients died during the intervention period, of whom 57% experienced early referral to specialist palliative care. The median days from referral to death was 130 (IQR: 53-359). Of the 209, 28 (13%) saw the Clinical Nurse Specialist and received Shared Care letters, and all (100%) had early specialist palliative care referral (median 240 days, IQR: 161-359). 21/209 (10%) saw the Clinical Nurse Specialist but had no Shared Care letter. Of these 21, 76% had early specialist palliative care referral (median 197 days, IQR: 96-251). 43/209 (21%) had a Shared Care letter but no interaction with the Clinical Nurse Specialist. Of these 43, 53% had early specialist palliative care referral (median 102 days, IQR: 53-257). 117/209 (56%) did not interact with the Clinical Nurse Specialist or have a Shared Care letter. Of these 117, 45% had early specialist palliative care referral (median 86 days, IQR: 40-204). Conclusions: The Clinical Nurse Specialist was associated with the greatest increase in early specialist palliative care referral; however, the Clinical Nurse Specialist and Shared Care letters combined were associated with even greater (100%) early specialist palliative care use.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.475
GPT teacher head0.578
Teacher spread0.103 · 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 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

Citations1
Published2022
Admission routes2
Has abstractyes

Explore more

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