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Record W2794342229 · doi:10.1177/0840470417747003

Patient and family engagement in Alberta Health Services: Improving care delivery and research outcomes

2018· article· en· W2794342229 on OpenAlex
Sarah Singh, Katharina Kovacs Burns, Jennifer Rees, Deanna Picklyk, Jessica Spence, Nancy Marlett

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealthcare Management Forum · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsHealth care deliveryHealthcare deliveryHealth services researchHealth careNursingHealth servicesOutcomes researchBusinessFamily medicineMedicineEnvironmental healthAlternative medicinePublic healthPolitical science

Abstract

fetched live from OpenAlex

Engaging patients and families in research and the design of quality improvement is an essential component of Patient and Family Centred Care (PFCC). Alberta Health Services (AHS) has been engaging patients and families to promote a cultural shift towards PFCC. The AHS trains patient and family advisors to share their experiences and encourages staff to work with advisors to co-design improvements in care. This article briefly describes the role and growth of patient and family advisors, advisory groups, and the participation of advisors in research initiatives through AHS’ Strategic Clinical Networks TM . It also describes recent efforts to build AHS’ patient and family engagement capacity by introducing standard patient engagement training, supporting the creation of the innovative Patient and Community Engagement Research internship program, and by developing tools to measure the impact of patient and advisors on AHS. And finally, this article provides key learnings for health leaders.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.154
GPT teacher head0.442
Teacher spread0.288 · 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