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Record W2901176220 · doi:10.12927/hcq.2018.25626

Patient and Staff Engagement in Health System Improvement: A Qualitative Evaluation of the Experience-Based Co-design Approach in Canada

2018· article· en· W2901176220 on OpenAlexaffabout
Kate Bak, Lesley Moody, Sarah Wheeler, Julie Gilbert

Bibliographic record

VenueHealthcare Quarterly · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsCancer Care Ontario
Fundersnot available
KeywordsNursingPatient experienceHealth careQualitative researchBest practiceMedicineQuality managementMedical educationBusinessMarketingPolitical scienceSociology

Abstract

fetched live from OpenAlex

Surveys and interviews were undertaken in Ontario, Canada, with healthcare staff, patients, caregivers and family members to evaluate the adoption and effectiveness of the experience-based co-design (EBCD) approach. EBCD combines patient and staff experiences to identify opportunities for healthcare improvement. Participants reported that EBCD was an effective form of improving experience. Implementation barriers included time, human resources and funding. Suggestions for increased EBCD utilization included funding, training, promotion of success stories, leadership and greater participant involvement. EBCD can be an effective method of identifying and transforming how healthcare services are delivered to improve the patient, caregiver and family experience.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.267
GPT teacher head0.454
Teacher spread0.187 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations17
Published2018
Admission routes2
Has abstractyes

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