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Record W2936460101 · doi:10.1097/mlr.0000000000001084

A Decade in Review

2019· article· en· W2936460101 on OpenAlexaffabout
Lisa Barbera, Lesley Moody

Bibliographic record

VenueMedical Care · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsCancer Care OntarioUniversity of Calgary
Fundersnot available
KeywordsGeneral partnershipIntervention (counseling)MedicinePlan (archaeology)MEDLINENursingBusiness

Abstract

fetched live from OpenAlex

BACKGROUND: In 2007 Cancer Care Ontario (CCO) implemented standardized systematic symptom evaluation in all cancer patients in Ontario using the Edmonton Symptom Assessment System. The initial implementation did not include symptom management guidance and this limited the success of the implementation. Within a short time, the need for guidance on how to respond to symptoms became apparent. OBJECTIVE: To describe how CCO has approached electronic symptom monitoring and related clinical response to symptom scores. RESULTS: CCO's approach to symptom management includes acknowledgment, assessment, and intervention steps. In partnership with the Program in Evidence Based Care, CCO developed guidance documents for management of each of the symptoms assessed with Edmonton Symptom Assessment System. These materials included an in-depth document similar to the full guidelines created by Program in Evidence Based Care for cancer treatment topics, a shorter pocket guide, and a 1-page algorithm. The guidance was aligned with symptom score severity. The 1-page algorithm was the most popular format of these materials. When time for revisions came, only this document was revised. When additional PRO measures were implemented, the plan ensured that the launch included a bundle of clinician-facing and patient-facing guidance materials together with the measure. All resources are accessible from a mobile-friendly website. CONCLUSIONS: Providing clear guidance for symptom management is an important part of successful PRO measure implementation. Involving a wide range of stakeholders early in the creation of such resources facilitates implementation and team building.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.010
GPT teacher head0.312
Teacher spread0.302 · 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 designNot applicable
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

Citations12
Published2019
Admission routes2
Has abstractyes

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