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Record W2905523720 · doi:10.12927/hcq.2018.25636

Evaluating Patient, Family and Public Engagement in Health Services Improvement and System Redesign

2018· article· en· W2905523720 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealthcare Quarterly · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsCanadian Foundation for Healthcare Improvement
Fundersnot available
KeywordsPublic healthPublic engagementPublic relationsKey (lock)Process managementBusinessHealth servicesService (business)Best practiceKnowledge managementMedicineNursingPolitical scienceMarketingComputer scienceEnvironmental healthComputer security

Abstract

fetched live from OpenAlex

As efforts to actively involve patients, family members and the broader public in health service improvement and system redesign have grown, increasing attention has also been paid to evaluation of their engagement in the health system. We discuss key concepts and approaches related to evaluation, drawing particular attention to different and potentially competing goals, stakeholders and epistemological entry points. Evaluation itself can be supported by an increasing number of frameworks and tools, matched to the relevant purpose and approach. The patient engagement evaluation field faces several challenges, including the need for greater specification of both the form and the context of engagement, the need to balance the measurement imperative with the relational aspects of care and the need for supportive organizations with the capacity and commitment to undertake high-quality engagement and its evaluation.

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.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.256
GPT teacher head0.454
Teacher spread0.197 · 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