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Record W6986270018

Patient/user perceptions on the principles of integration

2016· other· en· W6986270018 on OpenAlexaboutno aff

Bibliographic record

VenueLume (Universidade Federal do Rio Grande do Sul) · 2016
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMachine Learning in Bioinformatics
Canadian institutionsnot available
Fundersnot available
KeywordsFocus groupVariety (cybernetics)PerceptionHealth careCorporate governancePerspective (graphical)Qualitative propertyPopulationQualitative research
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Ten key principles have been identified to facilitate successful health systems integration.The principles include: 1) comprehensive services, 2) patient focus, 3) geographic coverage and rostering, 4) standardized care delivery through interprofessional teams, 5) performance management, 6) information technology, 7) organizational culture and leadership, 8) physician integration, 9) governance structure, and 10) financial management.To our knowledge, there is little research on patients/user' perceptions on the concept of integration.This unique perspective will assist in identifying the relevancy of the principles for patients and users as well as influence recommendations for which indicators should be prioritized for measurement and further research.Methods: As a part of a larger study to identify indicators and tools for measuring health systems integration, three focus groups were conducted with 17 patients/users of the system in three regions (British Columbia and Alberta, Canada, and Rio Grande do Sul, Brazil).Each focus group targeted a different population to capture a variety of perspectives.In British Columbia participants were from rural communities, in Alberta from a large urban setting and in Rio Grande do Sul participants represented the community Health Councils in the City of Porto Alegre.Participants were provided with a list and descriptions of the 10 integration principles.At the end of the session they were asked to prioritize the principles.Both quantitative and qualitative analysis of the data were completed.A virtual meeting was held to discuss similarities and differences in themes.Key sections of data from Brazil was translated into English to be included in our final analysis.Results: The highest priority principles for integration in Canada were patient focus, comprehensive services across the care continuum, and standardized care delivery through interprofessional teams.In Canada, focus groups participants felt the system was still provider and rd World Congress on Integrated Care, Mexico City, Mexico, 19-21 November, 2015 Conclusión: De acuerdo a los participantes los principios de mayor prioridad de la integración en Canadá y Brasil eran enfocados en pacientes y servicios integrales en todo el continuo cuidado.Equipo: Este proyecto de colaboración canadiense y brasileño incluye investigadores del conocimiento de los usuarios con experiencia en la política de los sistemas de salud y la planificación, revisiones sistemáticas, y las ciencias de la biblioteca.Integración de sistemas de salud es una prioridad en ambos países.La asociación se basa en elementos comunes, tales como: sistemas de salud financiados con fondos públicos; prioridades de financiamiento comparables; y la geografía similar con los grandes centros urbanos y comunidades rurales.La realización de la investigación colaborativa en estos dos países aumentará la aplicabilidad internacional de los 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)0.010
metaresearch head score (Gemma)0.024
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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
Published2016
Admission routes1
Has abstractyes

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