145 The British Society for Rheumatology’s Choosing Wisely UK recommendations
Notice bibliographique
Résumé
Background: The Choosing Wisely UK campaign aims to promote shared decision making between patients and clinicians, helping people choose care that is supported by evidence, free from harm, truly necessary and consistent with their values. The Academy of Medical Royal Colleges (AoMRC), which coordinates the campaign, invited the BSR to submit 3-6 recommendations in 2018. The audience includes patients; rheumatologists and other physicians; GPs; nurses ad allied health professionals. Methods: The 14-member working group included two patient contributors, one consultant nurse, six consultant rheumatologists, one GP staff grade rheumatologist, two rheumatology trainees and two immunologists. The National Rheumatoid Arthritis Society and Versus Arthritis were represented. The working group was convened and recommendation development completed within 12 weeks. For the first part of the abbreviated Delphi-exercise, working group members submitted proposed recommendations with an accompanying evidence summary. These were collated and distributed (verbatim and anonymously) to the group to inform a ranking exercise. Members rated each topic from 5 (highest) to 1 (lowest) anonymously and left remaining topics unscored; topics with the highest scores were selected. A subgroup, including patient contributors, met to draft the recommendations. Evidence summaries were collated from information submitted in the initial proposals and from further contributions from working group members. External experts were consulted on each recommendation, following which consensus was sought from the working group to ratify the recommendations. Results: Thirty-two proposals were received on 14 discrete clinical topics, from 10 working group members. Twelve members ranked topics. Six final recommendations were developed, all of which were endorsed by the BSR. The AoMRC accepted all six recommendations, proposing that ANA+ENA and C3/C4/dsDNA had clinician facing-recommendations only, due to their technical nature (table 1). Conclusion: Six recommendations were developed by a multidisciplinary team including people with arthritis. Because of the robust development process, we believe these recommendations are acceptable, meaningful and practical. Their application will lead to more personalised care, increased patient and clinician satisfaction, and better use of limited resources. We encourage all BSR members to engage with and champion these recommendations to inform shared decision-making conversations with patients. BSR Choosing Wisely UK Recommendations Disclosures: C.A. Sharp: Grants/research support; Charlotte A Sharp is supported by the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care (NIHR CLAHRC) Greater Manchester. I.N. Bruce: Honoraria; Ian N Bruce has received honoraria and/or grant funding from GSK, Eli Lilly, Astra Zeneca and Merck Serono. Grants/research support; Ian N Bruce has received honoraria and/or grant funding from GSK, Eli Lilly, Astra Zeneca and Merck Serono. B.M. Ellis: None. S. Elkhalifa: None. J. Galloway: None. B. Mulhearn: None. J. Firth: None. J. Fox: None. C. Mukhtyar: None. D.J. Murphy: None. A. Rowbottom: None. N. Snowden: None. K. Staniland: None. E. MacPhie: Honoraria; E.M. has been sponsored to attend international meetings by Pfizer and Roche, has accepted honoraria for educational meetings from Pfizer and Roche, her department has received sponsorship from Pfizer.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,023 | 0,081 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,011 | 0,004 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,017 | 0,014 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,063 | 0,041 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».