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Record W3011367542 · doi:10.1017/s0266462320000094

Defining the role of the public in Health Technology Assessment (HTA) and HTA-informed decision-making processes

2020· article· en· W3011367542 on OpenAlexaff
Jackie Street, Tania Stafinski, Edilene Lopes, Devidas Menon

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTerminologyCLARITYContext (archaeology)Health technologyPublic relationsPublic interestPublic participationProcess (computing)AccountabilityPolitical scienceHealth careComputer scienceLaw

Abstract

fetched live from OpenAlex

OBJECTIVES: The terminology used to describe community participation in Health Technology Assessment (HTA) is contested and frequently confusing. The terms patients, consumers, public, lay members, customers, users, citizens, and others have been variously used, sometimes interchangeably. Clarity in the use of terms and goals for including the different groups is needed to mitigate existing inconsistencies in the application of patient and public involvement (PPI) across HTA processes around the world. METHODS: We drew from a range of literature sources in order to conceptualize (i) an operational definition for the "public" and other stakeholders in the context of HTA and (ii) possible goals for their involvement. Draft definitions were tested and refined in an iterative consensus-building process with stakeholders from around the world. RESULTS: The goals, terminology, interests, and roles for PPI in HTA processes were clarified. The research provides rationales for why the role of the public should be distinguished from that of patients, their families, and caregivers. A definition for the public in the context of HTA was developed: A community member who holds the public interest and has no commercial, personal, or professional interest in the HTA process. CONCLUSIONS: There are two distinct aspects to the interests held by the public which should be explicitly included in the HTA process: the first lies in ensuring democratic accountability and the second in recognising the importance of including public values in decision making.

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)0.007
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.752
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.100
GPT teacher head0.465
Teacher spread0.366 · 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

Citations41
Published2020
Admission routes1
Has abstractyes

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