Computer-Based Stratified Primary Care for Musculoskeletal Consultations Compared With Usual Care: Study Protocol for the STarT MSK Cluster Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Musculoskeletal (MSK) pain is a major cause of pain and disability. We previously developed a prognostic tool (Start Back Tool) with demonstrated effectiveness in guiding primary care low back pain management by supporting decision making using matched treatments. A logical next step is to determine whether prognostic stratified care has benefits for a broader range of common MSK pain presentations. OBJECTIVE: This study seeks to determine, in patients with 1 of the 5 most common MSK presentations (back, neck, knee, shoulder, and multisite pain), whether stratified care involving the use of the Keele Start MSK Tool to allocate individuals into low-, medium-, and high-risk subgroups, and matching these subgroups to recommended matched clinical management options, is clinical and cost-effective compared with usual nonstratified primary care. METHODS: This is a pragmatic, two-arm parallel (stratified vs nonstratified care), cluster randomized controlled trial, with a health economic analysis and mixed methods process evaluation. The setting is UK primary care, involving 24 average-sized general practices randomized (stratified by practice size) in a 1:1 ratio (12 per arm) with blinding of trial statistician and outcome data collectors. Randomization units are general practices, and units of observation are adult MSK consulters without indicators of serious pathologies, urgent medical needs, or vulnerabilities. Potential participant records are tagged and individuals invited using a general practitioner (GP) point-of-consultation electronic medical record (EMR) template. The intervention is supported by an EMR template (computer-based) housing the Keele Start MSK Tool (to stratify into prognostic subgroups) and the recommended matched treatment options. The primary outcome using intention-to-treat analysis is pain intensity, measured monthly over 6 months. Secondary outcomes include physical function and quality of life, and an anonymized EMR audit to capture clinician decision making. The economic evaluation is focused on the estimation of incremental quality-adjusted life years and MSK pain-related health care costs. The process evaluation is exploring a range of potential factors influencing the intervention and understanding how it is perceived by patients and clinicians, with quantitative analyses focusing on a priori hypothesized intervention targets and qualitative approaches using focus groups and interviews. The target sample size is 1200 patients from 24 general practices, with >5000 MSK consultations available for anonymized medical record data comparisons. RESULTS: Trial recruitment commenced on May 18, 2018, and ended on July 15, 2019, after a 14-month recruitment period in 24 GP practices. Follow-up and interview data collection was completed in February 2020. CONCLUSIONS: This trial is the first attempt, as far as we know, at testing a prognostic stratified care approach for primary care patients with MSK pain. The results of this trial should be available by the summer of 2020. TRIAL REGISTRATION: ISRCTN Registry ISRCTN15366334; http://www.isrctn.com/ISRCTN15366334. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17939.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».