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Record W2109154160 · doi:10.1016/j.gaceta.2012.01.010

Reinversión en sanidad: fundamentos, aclaraciones, experiencias y perspectivas

2012· article· es· W2109154160 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGaceta Sanitaria · 2012
Typearticle
Languagees
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsExcuseDisinvestmentIgnoranceContext (archaeology)ObligationMeaning (existential)Government (linguistics)Political sciencePublic relationsBusinessGeographyPsychologyLaw

Abstract

fetched live from OpenAlex

En estos tiempos de crisis económica aumenta mucho más la presión por reducir el gasto como medida aislada que por aplicar fórmulas para maximizar la eficiencia de los servicios sanitarios. Disponemos de información, métodos y experiencias para obtener mejores resultados en salud con los recursos disponibles. En varios países se han adoptado diversas medidas para hacerlo. Una de ellas es la reinversión (también conocida como desinversión). Al tratarse de una táctica necesaria, pero compleja, alergénica y a menudo confundida, en este artículo se aclara su significado, se enmarca en su debido contexto y se describen los métodos y criterios empleados para identificar y priorizar las tecnologías médicas candidatas a la reinversión. Incluido el caso de España, se revisan las experiencias en reinversión de Nueva Zelanda, Australia, Canadá, Reino Unido e Italia, los obstáculos que afrontan y sus perspectivas a medio plazo. El desconocimiento no debería eximir socialmente de su aplicación, estemos o no en crisis. La mejora de la eficiencia social es una obligación del Sistema Nacional de Salud. During the economic crisis, the pressure to reduce health services expenditure as an isolated measure is greater than measures intended to increase the efficiency of these services. Information, methods and experiences to improve health outcomes with limited resources are available and a number of countries have been applying measures to achieve this goal. One of these measures is disinvestment. Given that this tactic is necessary but also intricate, allergenic and confusing, this article tries to clarify its meaning, place it in its correct context, and describe the methods and criteria used to identify and prioritize candidate medical technologies for disinvestment. The experiences of Spain, New Zealand, Australia, Canada, the United Kingdom and Italy in this endeavor are reviewed, as well as the obstacles faced by these countries when disinvesting and their mid-term perspectives. Ignorance does not excuse its application, regardless of whether there is a crisis or not. Efforts to improve social efficiency are a permanent obligation of the national health system.

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.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.026

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 head0.246
GPT teacher head0.419
Teacher spread0.173 · 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