TRABAJO ACADEMICO EN RED EN TORNO A LA TOMA DE DECISIONES EN SALUD ACADEMIC NETWORK RELATED TO HEALTH DECISION MAKING. ACADEMIC HEALTH DECISION SUPPORT NETWORK
Bibliographic record
Abstract
La Escuela de Enfermería de la Pontificia Universidad Católica de Chile (PUC) ha desarrollado, desde 1983, un modelo de atención de salud basado en el autocuidado (Lange I., Jaimovich S. 1996). Esta línea de trabajo fue enriquecida con el marco conceptual de apoyo a la toma de decisiones en salud desarrollado a partir de la década del noventa por O’Connor et al. Con el apoyo de estos autores, se inició el proyecto “Elecciones y decisiones en salud: una alianza profesional/usuaria con transferencia tecnológica canadiense chilena” (DECIDE), financiado por la Agencia Canadiense de Desarrollo Internacional (ACDI). Este proyecto incluyó una fase de trabajo colaborativo con otras escuelas de enfermería del país para incorporar el marco conceptual y la tecnología de apoyo a la toma de decisiones en salud en la formación de los futuros profesionales. Esta experiencia generó un modelo de trabajo en redes que permitió enriquecerla y ampliar la cobertura del proyecto, respetando individualidades e intereses de las escuelas participantes. Su sistematización permitió desarrollar un modelo de educación continua semipresencial en “Apoyo a la toma de decisiones en salud” que puede ser utilizado para capacitar enfermeras y otros profesionales de la salud de América Latina. Este artículo da a conocer el proceso vivido y las lecciones aprendidas, con el fin de demostrar que el trabajo en redes es una estrategia eficiente y factible para potenciar el desarrollo en enfermería The School of Nursing at the Catholic University of Chile (PUC) has been implementing, since 1983 a health care model based on selfcare. (Lange I., Jaimovich S.1996). This work has been enriched with the Ottawa Health Decision Support framework developed in the nineties, in Canada, by O’Connor, A. et al. With the support of the Canadian team and the financial support of the Canadian International Development Agency (CIDA) the project “Making Choices, Making Decisions: A Client/Provider Partnership in Canadian/Chilean Technology Transfer” (DECIDE) was carried out in Chile between 1999 and 2003. The dissemination phase of this project included collaboration with other schools of nursing to promote the incorporation of the Ottawa Decision Support Framework and tool kits for decision support into the nursing curriculum. This experience generated a networking model among the Schools, which enriched and strengthened the DECIDE project, regarding identity, pace and particular interests of each participating institution. As a result of this networking experience, a continuing education program was developed to improve the decision support skills of health professionals to improve the decision making abilities of their clients. This “semi presential” continuing education program will be useful to train health professionals in other Latin American countries as it incorporates distance learning methodologies. This article describes the networking process among 6 schools of nursing of different regions of Chile and the lessons learned. It demonstrates that networking is an efficient and feasible strategy to strengthen and potentialize nursing development
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.025 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".