Characterization and Evaluation of Department of Veterans Affairs Commission on Accreditation of Rehabilitation Facilities–Accredited Interdisciplinary Pain Rehabilitation Programs: Protocol for a Mixed Methods Program Evaluation
Notice bibliographique
Résumé
BACKGROUND: Veterans are more likely to experience chronic pain than civilians, with significant negative impacts on long-term health outcomes. Evidence for the effectiveness of prescription opioids for chronic pain management is limited, and chronic use of opioids is associated with an increased risk of sleep-disordered breathing, cardiovascular complications, and bowel dysfunction, as well as opioid misuse and overdose. Veterans Affairs (VA) and Department of Defense guidelines are prioritizing low-risk, evidence-based interdisciplinary pain management strategies while optimizing pain-related outcomes (PRO) for veterans. Commission on Accreditation of Rehabilitation Facilities (CARF)-Accredited VA Interdisciplinary Pain Rehabilitation Programs (IPRPs) have shared characteristics, while maintaining their unique characteristics as individual pain management programs. Though little is known about the characteristics of VA's IPRPs (eg, staffing, services, and patients served), implementation, and sustainability of these mandated programs. OBJECTIVE: The goals of our operational partner-driven evaluation are to (1) characterize IPRPs across multiple program factors, including but not limited to, service delivery methods, team composition, program characteristics, services and modalities offered, and patients served; (2) triangulate data to inform data visualization that characterizes and illustrates the IPRPs individually and collectively as a system of care; and (3) identify patient-reported outcomes (PROs) and metrics to measure program effectiveness and determine overlap across IPRPs. METHODS: This partnered-driven program evaluation will use a sequential mixed methods prospective design, including interviews and surveys. The Consolidated Framework for Implementation Research (CFIR), Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, and Expert Recommendations for Implementing Change (ERIC) strategies will be used to contextualize qualitative data. Rapid content analysis will be used to iteratively analyze qualitative data, while descriptive statistics will be used to analyze quantitative data. Datasets will be triangulated to support data visualization for partners to inform clinical and operational decision support. RESULTS: As of April 2025, All IPRP sites are engaged, and survey and interview data have been collected and prepared for analysis. The results and deliverables will inform VA CARF-accredited IPRP characterization, evaluation, and implementation as a learning health system. CONCLUSIONS: The results of this evaluation will characterize CARF-accredited IPRPs and identify determinants affecting the implementation of this complex intervention, made up of multiple evidence-based practices. Partner-driven data will inform the state of implementation at each site, and quantitative measures will provide options for collecting standardized outcome measures for continued program evaluation. This operational partner-driven evaluation will inform future efforts for quality improvement to improve veterans' pain management outcomes. This protocol informs the use of a mixed methods approach to evaluate a multimodal intervention (ie, IPRP), made up of multiple evidence-based practices to treat a complex comorbid condition. Future work may include data management infrastructure development and cost evaluations to inform clinical and operational decision-making. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/72091.
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 | 0,110 | 0,110 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,003 |
| Méta-épidémiologie (sens large) | 0,005 | 0,008 |
| Bibliométrie | 0,006 | 0,007 |
| Études des sciences et des technologies | 0,007 | 0,004 |
| Communication savante | 0,007 | 0,005 |
| Science ouverte | 0,005 | 0,005 |
| Intégrité de la recherche | 0,004 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,038 | 0,007 |
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 ».