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Record W4409341002 · doi:10.1186/s12913-025-12582-3

Measuring person-centred care in the mission, vision, and core value statements of Canadian healthcare organizations

2025· article· en· W4409341002 on OpenAlexaffabout
Iqmat Iyiola, Sadia Ahmed, Paul Fairie, Matthew Luzentales-Simpson, Kimberly Manalili, Maria Santana

Bibliographic record

VenueBMC Health Services Research · 2025
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsUniversity of CalgaryCanadian Patient Safety Institute
Fundersnot available
KeywordsHealth administrationHealth informaticsNursing researchHealth careMedicineCore (optical fiber)Public healthValue (mathematics)NursingHealth services researchPolitical scienceComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Person-centred care (PCC) has been shown to improve health outcomes. The inclusion and incorporation of person-centredness in care has been a growing priority for healthcare organizations across Canada. METHODS: Person-Centred Care Quality Indicators (PC-QI) evaluate to what extent various PCC elements have been integrated into healthcare organizations. Using the first PC-QI, content analysis was performed on the mission, vision, and core value statements of 54 healthcare organizations to assess whether PCC is being included as a strategic and decision-making priority in the Canadian healthcare system. RESULTS: Fifty-three healthcare organizations (98%) included at least one domain of PCC in their statements. The three most frequent were compassionate care (85%), trusting relationship with providers (70%), and co-designed care (56%). There was no presence of affordable care. CONCLUSION: Canadian healthcare organizations are working towards promoting and implementing a culture that prioritizes some elements of PCC in the care of patients.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.041
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0040.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.381
GPT teacher head0.528
Teacher spread0.147 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations1
Published2025
Admission routes2
Has abstractyes

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