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Record W2518308679 · doi:10.1136/bmjopen-2016-011918

Do choosing wisely tools meet criteria for patient decision aids? A descriptive analysis of patient materials

2016· article· en· W2518308679 on OpenAlexaffabout
France Légaré, Jessica Hébert, Larissa Goh, Krystina B. Lewis, Maria Ester Leiva Portocarrero, Hubert Robitaille, Dawn Stacey

Bibliographic record

VenueBMJ Open · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsOttawa HospitalUniversity of OttawaHôpital Saint-François d'Assise
Fundersnot available
KeywordsMedicineDecision aidsDescriptive statisticsDecision analysisMedical emergencyMedical educationAlternative medicineStatistics

Abstract

fetched live from OpenAlex

OBJECTIVES: Choosing Wisely is a remarkable physician-led campaign to reduce unnecessary or harmful health services. Some of the literature identifies Choosing Wisely as a shared decision-making approach. We evaluated the patient materials developed by Choosing Wisely Canada to determine whether they meet the criteria for shared decision-making tools known as patient decision aids. DESIGN: Descriptive analysis of all Choosing Wisely Canada patient materials. DATA SOURCE: In May 2015, we selected all Choosing Wisely Canada patient materials from its official website. MAIN OUTCOMES AND MEASURES: Four team members independently extracted characteristics of the English materials using the International Patient Decision Aid Standards (IPDAS) modified 16-item minimum criteria for qualifying and certifying patient decision aids. The research team discussed discrepancies between data extractors and reached a consensus. Descriptive analysis was conducted. RESULTS: Of the 24 patient materials assessed, 12 were about treatments, 11 were about screening and 1 was about prevention. The median score for patient materials using IPDAS criteria was 10/16 (range: 8-11) for screening topics and 6/12 (range: 6-9) for prevention and treatment topics. Commonly missed criteria were stating the decision (21/24 did not), providing balanced information on option benefits/harms (24/24 did not), citing evidence (24/24 did not) and updating policy (24/24 did not). Out of 24 patient materials, only 2 met the 6 IPDAS criteria to qualify as patient decision aids, and neither of these 2 met the 6 certifying criteria. CONCLUSIONS: Patient materials developed by Choosing Wisely Canada do not meet the IPDAS minimal qualifying or certifying criteria for patient decision aids. Modifications to the Choosing Wisely Canada patient materials would help to ensure that they qualify as patient decision aids and thus as more effective shared decision-making tools.

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)0.057
metaresearch head score (Gemma)0.305
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.302

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0570.305
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.736
GPT teacher head0.625
Teacher spread0.111 · 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".

Quick stats

Citations22
Published2016
Admission routes2
Has abstractyes

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