Evaluating Patient Experience With Genomic Medicine: A Content Analysis of National Cancer Institute–Designated Cancer Centers’ Websites
Notice bibliographique
Résumé
Background: National Cancer Institute-designated cancer centers (NCI-CCs) throughout the United States are mandated to translate state-of-the-art cancer research to communities and enhance clinical care for patients within their catchment areas. NCI-CCs play a vital role in national cancer initiatives focused on optimizing cancer care via personalized medicine in which improved risk assessment, screening, and genetic testing are foundational. In this era of targeted personalized care, although genetics has been incorporated into cancer centers, it is unknown how these innovations are being communicated to the public and communities served on cancer center websites. There is particularly limited knowledge surrounding how NCI-CCs publicly communicate their efforts to integrate patient-reported experiences with genomics to fulfill their overall mission and reduce the cancer burden in their catchment areas. Objective: The objective of this study was to evaluate how NCI-CCs publicly share information on their websites related to cancer center programming and activities to measure and incorporate patients' experiences with the use of genetics to guide cancer care. Methods: For all NCI-CCs providing clinical care (N=65), we conducted a review of publicly available and published information and assessed five domains relevant to patients' experiences with genomic medicine: whether NCI-CCs (1) provided genetic testing, (2) directly expressed a goal of delivering personalized care, (3) provided pharmacogenomic testing, (4) assessed patient-reported experience measures with genomic medicine (including patient-reported outcomes [PROs] and other patient experience measures [OPEMs]), and (5) indicated an established infrastructure or set of resources to evaluate patient experience. We conducted a content analysis of the publicly available websites of NCI-CCs using the validated directed approach to content analysis. We quantified the results of our content analysis using count measures based on a binary (yes or no) coding scheme. Results: While almost all the NCI-CCs (64/65, 98%) discussed providing personalized care and performing genetic testing on their websites, we found that 58% (38/65) indicated online that they assessed PROs or other patient experience measures with genomic medicine. Fewer centers (25/65, 38%) discussed on their websites having a mechanism for evaluating patients' experiences with genomic medicine that captured broader types of information beyond PROs, such as measures of patient education or care team communication. Finally, approximately 1 in 3 NCI-CCs (23/65, 35%) indicated having an established infrastructure with departmental resources dedicated to monitoring patients' experiences. These centers reflecting a built-in infrastructure were 8% to 12% more likely to publicly communicate targeted activities to assess patients' experiences with genomic medicine. Conclusions: With the burgeoning use of genomics in research and clinical care, comprehensive evaluation and incorporation of measures of patients' experiences with genomic medicine present a key opportunity to enhance cancer care at NCI-CCs.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 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 ».