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Record W2107647612 · doi:10.12927/cjnl.2002.19147

Building a Dream: Creating an Oncology Day/Evening Hospital

2002· article· en· W2107647612 on OpenAlexaffvenue
Katie Fletcher, Vivian Painter

Bibliographic record

VenueNursing leadership · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsCancerCare Manitoba
Fundersnot available
KeywordsMedicineAmbulatoryEveningAmbulatory careInpatient careModalitiesEconomic shortageIntensive care medicineEmergency medicineHealth careMedical emergencyInternal medicine

Abstract

fetched live from OpenAlex

The demand for inpatient beds has reached and often exceeds capacity producing waiting lists for cancer care. There is a need to explore alternative approaches to oncology treatment. The Oncology Day/Evening Hospital (ODEH), originally envisioned in 1995 as a joint project between an ambulatory cancer centre and a large teaching hospital, is an important cancer treatment initiative offering extended hours of ambulatory oncology treatment on days, evenings, weekends and statutory holidays. A review of current inpatient treatment modalities revealed that many patients receiving inpatient therapy could be safely and effectively managed in the ambulatory setting if treatment regimens were modified and if ambulatory hours of operation were extended. Healthcare improvements expected were: appropriate movement of inpatient activity to the ambulatory setting; more opportunities for patient choice in treatment time thereby allowing for maintenance of normal living; better quality of life for patients through prevention of hospitalization; decrease in treatment waiting times; consolidation of patients into an ambulatory oncology treatment setting as opposed to utilization of adult medicine units; and more rational inpatient bed utilization with reduction of admissions and intra-treatment transfers. This article describes our experience in building a dream, the challenges and lessons learned in implementing a better way to deliver oncology care in an environment of rapid change and staff shortages.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.207
GPT teacher head0.293
Teacher spread0.085 · 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 designTheoretical or conceptual
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

Citations2
Published2002
Admission routes2
Has abstractyes

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