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Record W2793303974 · doi:10.3917/rsi.131.0061

Développement d’un système de gestion de la performance des soins dans un centre hospitalier universitaire suisse

2018· article· fr· W2793303974 on OpenAlexaff
Joachim Rapin, Danielle D’Amour, Thierry Penseyres, Gabrielle Santos, Vincent Adatte, Isabelle Lehn, Cédric Mabire

Bibliographic record

VenueRecherche en soins infirmiers · 2018
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Studies show high variability in the quality of care and a significant incidence of adverse events. The care management direction of a university hospital center (CHU) has developed a care performance measuring system. The aim of the article is to present the different development stages of this system. The authors used May's Normalization Process Theory, which focuses on factors influencing the engagement of individuals, groups, and organizations in sustaining change.The CHU's approach led to the following results : 1) reaching a consensus on performance concept and identifying five areas of performance, 2) selection of 12 priority indicators to assess performance, 3) measures development, 4) setting up the method of collecting information 5) creation of a mechanism for analyzing the results by care teams and 6) dissemination of results via dashboards.The approach focuses on strategies for mobilizing managers and health care teams. Specific recommendations relate to the need to provide expert resources, review clinical guidance and ensure accountability of health care providers.

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)0.018
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0010.001

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 head0.214
GPT teacher head0.465
Teacher spread0.251 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2018
Admission routes1
Has abstractyes

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