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Record W2110289143 · doi:10.1186/1472-6963-10-228

Public views on a wait time management initiative: a matter of communication

2010· article· en· W2110289143 on OpenAlexaffabout
Rebecca A Bruni, Andreas Laupacis, Wendy Levinson, Douglas K. Martin

Bibliographic record

VenueBMC Health Services Research · 2010
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsHealth administrationPublic relationsPublic healthNursing researchHealth informaticsPublic involvementQualitative researchMedicineBusinessNursingSociologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Many countries have tried to reduce waiting times for health care through formal wait time reduction strategies. Our paper describes views of members of the public about a wait time management initiative--the Ontario Wait Time Strategy (OWTS) (Canada). Scholars and governmental reports have advocated for increased public involvement in wait time management. We provide empirically derived recommendations for public engagement in a wait time management initiative. METHODS: Two qualitative studies: 1) an analysis of all emails sent by the public to the (OWTS) email address; and 2) in-depth interviews with members of the Ontario public. RESULTS: Email correspondents and interview participants supported the intent of the OWTS. However they wanted more information about the Strategy and its actions. Interview participants did not feel they were sufficiently made aware of the Strategy and email correspondents requested additional information beyond what was offered on the Strategy's website. Moreover, the email correspondents believed that some of the information that was provided on the Strategy's website and through the media was inaccurate, misleading, and even dishonest. Interview participants strongly supported public involvement in the OWTS priority setting. CONCLUSIONS: Findings suggest the public wanted increased communication from and with the OWTS. Effective communication can facilitate successful public engagement, and in turn fair and legitimate priority setting. Based on the study's findings we developed concrete recommendations for improving public involvement in wait time management.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.004

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 head0.284
GPT teacher head0.538
Teacher spread0.254 · 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; both teacher heads agree on what is shown here.

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

Citations20
Published2010
Admission routes2
Has abstractyes

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