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Record W2334176549 · doi:10.1177/2165079915620201

Stakeholders’ Perspectives About and Priorities for Economic Evaluation of Health and Safety Programs in Healthcare

2016· article· en· W2334176549 on OpenAlexaff
Emile Tompa, Henriette de Boer, Sara Macdonald, Hasanat Alamgir, Mieke Koehoorn, Jaime Guzmán

Bibliographic record

VenueWorkplace Health & Safety · 2016
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsUniversity of British ColumbiaInstitute for Work & HealthMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsStakeholderHealth careBusinessDelphi methodOccupational safety and healthPatient safetyQuality (philosophy)NursingMedicinePublic relationsEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

This study identified and prioritized resources and outcomes that should be considered in more comprehensive and scientifically rigorous health and safety economic evaluations according to healthcare sector stakeholders. A literature review and stakeholder interviews identified candidate resources and outcomes and then a Delphi panel ranked them. According to the panel, the top five resources were (a) health and safety staff time; (b) training workers; (c) program planning, promotion, and evaluation costs; (d) equipment purchases and upgrades; and (e) administration costs. The top five outcomes were (a) number of injuries, illnesses, and general sickness absences; (b) safety climate; (c) days lost due to injuries, illnesses, and general sickness absences; (d) job satisfaction and engagement; and (e) quality of care and patient safety. These findings emphasize stakeholders' stated priorities and are useful as a benchmark for assessing the quality of health and safety economic evaluations and the comprehensiveness of these findings.

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)0.016
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.608
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.243
GPT teacher head0.476
Teacher spread0.233 · 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.

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

Citations1
Published2016
Admission routes1
Has abstractyes

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