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Record W4389703363 · doi:10.1017/s0266462323002052

PP69 Health Technology Assessment And University Health Center Affiliation Agreement: Current Situation And Potential Developments In Quebec

2023· article· en· W4389703363 on OpenAlexaboutno aff
Marc Rhainds, Gisèle Irène Claudine Mbemba, Daniel La Roche, Marie‐Pierre Gagnon

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsMandateHealth technologyRelevance (law)Health careMedical educationPsychologyNursingMedicinePublic relationsPolitical science

Abstract

fetched live from OpenAlex

Introduction According to the Quebec law on health and social services, health technology assessment (HTA) is part of university hospital centers’ mission, together with training, research and care. However, unlike these other functions, HTA is not covered in current affiliation agreements that bind a university with academic health institutions. Université Laval and its affiliated health institutions set up a consultation committee whose mandate is to propose the terms of an agreement to specify collaboration regarding HTA between the university and its affiliated institutions. This study investigates perceptions and needs of stakeholders from Université Laval and its affiliated health institutions with respect to the HTA mission. Methods Semi-structured interviews were conducted with four types of participants, namely university faculty members, health professionals and managers from institutions with and without HTA units, as well as external partners. Interview guides were developed based on the integrated analysis framework of Greenhalgh et al., and adapted to each group of respondents. Most interviews were conducted in groups and were facilitated by a research associate and a senior investigator. Interviews were recorded and uploaded to NVivo 1.6.2 software for codification and analysis. Results A total of 57 people were interviewed (nine group interviews and 35 individual interviews). Three main themes emerged, namely knowledge of HTA, factors related to the relevance of the HTA function, and organizational factors. Results showed that half of the respondents have a vague knowledge of HTA or have never heard of it. Most of the respondents agreed that the HTA function fits well with the mission of a health institution. They would accept getting involved with HTA activities at different levels if all conditions are met. Nevertheless, almost half of respondents believed that others strategies than including HTA into contracts of affiliation should be explored to regulate this function. Finally, organizational obstacles such as the lack of funding, shortage of staff and the lack of well-structured collaborations were highlighted by respondents. Conclusions Despite recognition of the importance of the HTA function in university health centers, interventions will be required at different levels to support the development of local HTA capacity. In particular, popularization of the HTA function and collaboration networks through specific projects should be developed.

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)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.919
Threshold uncertainty score0.591

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.007
Science and technology studies0.0050.002
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.001

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 head0.120
GPT teacher head0.458
Teacher spread0.338 · 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 designNot applicable
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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