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Record W1916011242 · doi:10.1017/s0266462305050361

Use of health technology assessment in decision making: Coresponsibility of users and producers?

2005· article· en· W1916011242 on OpenAlexaffabout
Myriam Hivon, Pascale Lehoux, Jean‐Louis Denis, Stéphanie Tailliez

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsCredibilityHealth technologyHealth carePublic relationsKnowledge managementBusinessPsychologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

OBJECTIVES: Health technology assessment (HTA) is a policy-oriented form of research designed to inform decision-makers on the introduction, use, and dissemination of health technology. Whereas research on knowledge transfer has focused on knowledge producers, little attention has been given to the user's perspective. This study examines how health-care provider, administrator, and patient associations across Canada use HTA reports and the limitations they encounter when accessing and using scientific knowledge. METHODS: This study draws from semistructured interviews (n=42) conducted with three types of user, located in British Columbia, Alberta, Saskatchewan, Ontario, and Quebec. Applying well-established conceptual categories in knowledge utilization research, our qualitative analyses sought to define more precisely how HTA is used by interviewees as well as the most significant barriers they encounter. RESULTS: The vast majority of users recognize the usefulness and credibility of HTA reports. Of interest, the way they use HTA takes different forms. Although administrators and health-care providers are in a better position than patient associations to act directly on HTA messages--making an instrumental use of HTA--we also found conceptual and symbolic uses across all groups. Our results also indicate that significant organizational, scientific, and material limitations hinder the use of scientific evidence. Overcoming such barriers requires a greater commitment from both HTA producers and users. CONCLUSIONS: This study argues that, to ensure better uptake of HTA, it should become a shared responsibility between HTA producers and various types of user.

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 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)0.014
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.235
GPT teacher head0.516
Teacher spread0.281 · 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 teacher head, 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

Citations59
Published2005
Admission routes2
Has abstractyes

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Same venueInternational Journal of Technology Assessment in Health CareSame topicHealth Systems, Economic Evaluations, Quality of LifeFrench-language works237,207