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Record W7028170907

Evaluación a la calidad y seguridad en la atención a pacientes del servicio de medicina interna del Hospital Eugenio Espejo

2017· article· es· W7028170907 on OpenAlexaboutno aff

Bibliographic record

VenueRepositorio Institucional de la Universidad de las Fuerzas Armadas ESPE (Universidad de las Fuerzas Armadas ESPE) · 2017
Typearticle
Languagees
FieldEngineering
TopicPhysics and Engineering Research Articles
Canadian institutionsnot available
FundersUnited Nations
KeywordsAccreditationQuality (philosophy)Work (physics)Clinical Practice
DOInot available

Abstract

fetched live from OpenAlex

El objetivo del presente trabajo de investigación consistió en realizar un análisis de la calidad y seguridad de la atención médica en el Hospital de Especialidades Eugenio Espejo de la ciudad de Quito-Ecuador en el servicio de Medicina Interna, a través de un proceso de comparación entre la realidad evidenciada en el servicio objeto de estudio y estándares de calidad nacionales e internacionales de estructura, proceso y resultados, para el efecto de utilizaron tres instrumentos metodológicos como son la observación directa, la evaluación a historias clínicas y la entrevista no estructurada a usuarios internos y externos. Para evaluación de calidad en el presente proyecto de investigación se tomaron como base los estándares establecidos por la Accreditation Canada International (ACI) para evaluar proceso y los estándares de la OPS y la normativa peruana para evaluar estructura y resultados.

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)0.013
metaresearch head score (Gemma)0.030
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 score0.014
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.271
Teacher spread0.265 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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