Assessing the needs of those who serve the underserved: A national survey among cancer care clinicians.
Notice bibliographique
Résumé
175 Background: In 2009, ASCO confirmed that addressing cancer care disparities is critical for the Society and committed to approaches to eliminate such disparities. Yet, gaps remain in identifying the best approaches to do so. It remains unknown which cancer care providers serve patients from “underserved populations'' (defined as individuals who have historically received inadequate health care and health care services), what unmet needs they experience in their cancer care delivery, and how best to engage and support these providers. The objectives of this study were to explore challenges faced by providers serving underserved patients to inform development of a broader online survey and identify solutions that ASCO can implement to better support these providers. Methods: A multi-phase mixed-methods approach was utilized. Phase 1 involved key informant semi-structured interviews with 12 oncology providers caring for adult patients in the US from April to May 2021. Phase 2 involved survey development based on themes identified in Phase 1. The survey assessed: provider needs; processes for eliciting, documenting, and addressing social and economic needs of patients; and how ASCO could best support these providers. Phase 3 involved email distribution of the online survey in May 2022 to 5800 individuals identified through ASCO’s customer database. Eligibility criteria included providing care for adults with cancer in the US and prior consent to receive ASCO survey communications. Results: Of 477 respondents, the majority were ASCO members (88%), in an academic practice (57%), medical oncologists (77%), non-Hispanic (89%) and/or Caucasian/White (67%) and had > 15 years’ clinical experience (57%). A majority (60%) provided ≥25% of their clinical time providing cancer care to underserved populations and routinely engaged with administration to secure resources (61%) and local community organizations to obtain services (42%) for patients. Most (43-77%) indicated that a social worker/case manager was primarily responsible for addressing patient social needs. The majority reported that identification and dissemination of best practices (55%) and development of a return-on-investment business model (60%) would best help address patient needs. Some respondents expressed a desire to collaborate with ASCO on policy reform (32%) and for ASCO to help build or strengthen partnerships with local initiatives (29%). Conclusions: This is the first US-based survey assessing barriers and solutions to delivering cancer care among underserved populations. The findings from this work provide insights about how ASCO can help equip practices to address the social needs of their patients. Further work will be conducted to develop and implement suggested solutions.
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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».