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Record W4414482116 · doi:10.56294/hl2025882

Implementation of Good Practice Guidelines for Person- and Family-Centered Care in Primary Health Care in Chile

2025· article· en· W4414482116 on OpenAlexaboutno aff
María José Vásquez Mayr, Amália Graciela Silva Galleguillo, Mirliana Ramírez-Pereira, Valeria Díaz Videla, Angélica Villamán Guajardo, Esmérita Opazo-Morales

Bibliographic record

VenueHealth Leadership and Quality of Life · 2025
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsPillarHealth careScale (ratio)Primary carePrimary health careIntervention (counseling)Best practiceGood practice

Abstract

fetched live from OpenAlex

Introduction: Person- and family-centered care has become a fundamental pillar of Primary Health Care (PHC), promoting active participation, effective communication, and respect for autonomy. In this context, an implementation experience with the Registered Nurses' Association of Ontario (RNAO) Good Clinical Practice Guidelines (GCPG) was developed in a health center in Chile. Objective: To analyze the experience with the implementation of the GCPG "Person- and Family-Centered Care" at the Dr. Fernando Monckeberg Family Health Center (CESFAM). Methodology: A single-case study design was used. Data were collected through documentary analysis. The process was carried out in three phases, ensuring ethical feasibility and a thorough understanding of the phenomenon. Results: Three key GCPG recommendations were prioritized. Multi-format educational resources, a "Comprehensive Care Card," and a user satisfaction survey were developed. Eighty-two percent of staff were trained, and the survey was administered in 46 % of ECICEP check-ups. Ninety-six percent of respondents positively evaluated the care, with scores of 6 or 7 on a scale of 1 to 7. Discussion: Experience shows that it is possible to implement person-centered strategies in PHC, using evidence-based guidelines adapted to the local context. Challenges were identified, particularly with the coverage of user assessments. Conclusions: the intervention allowed for the integration of person-centered practices in a concrete and measurable way, generating valuable learning for future implementations in similar contexts.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.557
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.633
GPT teacher head0.578
Teacher spread0.055 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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