Defining Cancer Care Quality or Delivering Quality Cancer Care?
Notice bibliographique
Résumé
Many in the oncology world see as accepted that quality and value are difficult to define and that no specialty-wide consensus is likely to be reached in the short term about how to measure and report success at improving either.Others find the definition just beyond their grasp and suggest that, like pornography, they know it when they see it.Large organizations, publications, conferences, and processes have sprung up around the concept, and various attempts have been made to develop "measures of quality" that can characterize a practice or physician in this area.This work includes ongoing efforts within and among the National Quality Forum, NCCN, ASCO, The US Oncology Network (The Network), the Community Oncology Alliance, and Ontario Cancer Care to identify quality measures-many of which focus on surrogate processes or activities that should lead to quality.Instead, however, we believe this effort and investment should focus on outcomebased measures, and we offer a paradigm for measuring interventions:• Quality is the efficient delivery of evidence-based care by trained clinicians in an accessible setting.• In this context, value is providing higher quality care at the same cost, or the same quality at a lower cost.We believe these concepts are at the core of cancer care delivery, whether in the community or academic setting and across specialties, including medical oncology, radiation oncology, gynecologic oncology, urology, and surgery.Achieving quality will require integrated, coordinated care with clinical teams spanning these professionals and settings.It requires not only coordination among clinicians of different specialties but also investment in infrastructure resources to facilitate the integration of process development and clinical decision support tools that support evidence-based practices that optimize practice efficiency and care delivery.If the right investments have been made and communications highways created, these definitions are measurable, reportable, and comparable (without significant manual effort).Just as important, these definitions allow quality and value to evolve over time as the evidence evolves.Consequently, the highest-quality treatment pathways, and even the best modalities of treatment, may be vastly different in the future.For example, advance care planning and palliative care services would likely not have been included in the concept of evidence-based care 10 years ago.Today, however, the data suggest that palliative care concurrent with disease-directed care can improve outcomes and patient experiences while reducing costs.This view is also supported by a decade of hypothesis, consensus-building, technology investment, data collection, and analysis by physicians and supporting clinicians and staff of The Network, who we believe pioneered the concepts of narrowly drawn, evidence-based pathways for care in oncology.Nearly a decade ago, physicians in The Network decided to develop Level I Pathways, evidence-based guidelines that redirect the wide range of treatments in oncology care into more precise, clinically proven treatment options.(More information is available at http://www.usoncology.com/cancercareadvocates/
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 | 0,105 | 0,227 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,006 | 0,009 |
| Études des sciences et des technologies | 0,004 | 0,035 |
| Communication savante | 0,018 | 0,034 |
| Science ouverte | 0,005 | 0,008 |
| Intégrité de la recherche | 0,007 | 0,017 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».