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Record W2784227974 · doi:10.1017/s0266462317002896

PP142 A Mental Health Hospital-based Health Technology Assessment In Quebec, Canada: Structure And Products

2017· article· en· W2784227974 on OpenAlexaboutno aff
Ionela Gheorghiu, Alain Lesage, Adam Mongodin, Marlène Galdin

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsUnit (ring theory)OfficerMental healthHealth technologyNominationMedicineBusinessPsychologyHealth carePolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION: Our Hospital-based Health Technology Assessment unit (HB-HTA) was founded in 2011 following the nomination of Louis-H. Lafontaine hospital as the Montreal University Mental Health Institute (IUSMM). From the beginning, the HB-HTA has been supporting and advising the Chief Executive Officer of IUSMM in the decision-making process concerning the implementation of new technologies and practices in mental health. Since 2015, the HB-HTA is part of the East of Montreal Regional Integrated Health and Social Services Centre (CIUSSS de l'Est-de-l’Île de Montréal), continuing to support decisions in mental health. Currently, the HB-HTA unit is nested in the Quality, Performance and Ethics department. METHODS: Formed by a coordinator, a scientific advisor and a manager, the HB-HTA team plans, organizes and sets up the evaluation activities. The unit benefits from the support of a Steering Committee which consists of representatives of clinical, administrative and research directions, as well as of health users and families. This committee determine the strategic orientation of the HB-HTA unit, prioritize the projects, approves the evaluation products and gives indications on the knowledge transfer process. RESULTS: To answer the decision questions, our HB-HTA unit employs two types of products: evaluation reports and informative notes. Based on an exhaustive literature search and consultations with stakeholders, the evaluation reports offer recommendations to support the decision-making process. The informative notes are rapid responses based on a partial literature search. The nature of this type of analysis does not allow the formulation of recommendations, however, a conclusion of the consulted literature is offered. CONCLUSIONS: Based on the work of our HB-HTA unit, some important decisions were made by the IUSMM. As an example, the systematic screening of psychiatric patients for drug and alcohol was not favored by our institution; rather than this, priority was given to staff training, in order to better identify and treat psychiatric patients with substance abuse comorbidity.

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)0.014
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: none
Teacher disagreement score0.104
Threshold uncertainty score0.757

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.013
Science and technology studies0.0030.002
Scholarly communication0.0070.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0330.005

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 head0.077
GPT teacher head0.441
Teacher spread0.364 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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