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Record W4310830901 · doi:10.1017/9781009211086.025

Integrated People-Centered Health Care

2022· book-chapter· en· W4310830901 on OpenAlexaff
Katherine Rouleau, Shatha Albeik, Sayed Masoom Shah, Kenneth Yakubu, Akihiro Seita

Bibliographic record

VenueCambridge University Press eBooks · 2022
Typebook-chapter
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsKey (lock)Integrated careAgency (philosophy)Integrated servicesRefugeePublic relationsHealth carePalestinePolitical scienceMedicineBusinessKnowledge managementProcess managementSociologyComputer scienceComputer security

Abstract

fetched live from OpenAlex

The integration of people-centred services is key to improving the performance of health systems. This chapter explores the rationale and definitions of integrated and people-centred services, considers frameworks to inform and drive integrated care, and describes common barriers as well as enabling strategies related to values and policy, the engagement of key stakeholders and operational considerations. It highlights the unique role of family practice (also called family medicine) as a community-based and community-oriented discipline, and as a driver of comprehensive integrated people-centred care. It concludes with a description of the key strategies used in the re-organization of primary care services into a family health model by United Nations Relief and Works Agency for Palestine Refugees (UNRWA) in the Near East in 2011.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0060.005
Open science0.0020.009
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0370.010

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 head0.057
GPT teacher head0.316
Teacher spread0.259 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

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