Implementing standardized documentation for goals of care among advanced stage cancer patients.
Notice bibliographique
Résumé
e23236 Background: Early goals of care (GOC) discussions are associated with better health outcomes and quality of life for patients with advanced cancer. We describe a quality improvement initiative to improve documentation of GOC discussions. Methods: Using a Plan-Do-Study-Act model, we promoted use of a concise GOC documentation form developed by Cancer Care Ontario (CCO) among oncologists at a single institution. In stage 1, we established baseline data for 3 metrics within 60 days of initial consult: documented GOC discussions, documentated resuscitation status, and palliative care referral rates . Patients were identified by searching the hospital’s cancer activity level reporting database using ICD-10 codes for metastatic solid tumors and hematologic malignancies as well as the cases prescribed palliative systemic therapy. Corresponding patient charts were selected from the electronic health record (EHR) system and manually reviewed. In stage 2, the GOC documentation form was created with stakeholder input from patients, oncologists, nurses, social workers and palliative care physicians and implemented. In stage 3, we repeated the same approach as in stage 1 to obtain data for our metrics following implementation of the initiative and solicited feedback from patients and physicians. GOC forms in the EHR were manually reviewed to identify and track palliative referral status and resuscitation status completion. Results: At baseline, only 15 of 283 (5%) patients with incurable cancer had documented GOC discussions within 60 days of initial consult. 7 (2%) had DNR statuses documented and 11 (4%) consults were referred to palliative care. 83% of oncologist surveyed identified time-pressures as a reason for poor documentation rates. Following implementation, only 14 (2%) of 720 new consults had forms completed within 60 days. Patients who had the GOC form completed had a higher rate of palliative care referrals than those who did not (4.8% vs. 33%, p = 0.121). 140 GOC forms were completed in total. Among them, 90(64.3%) had a documented DNR and 48 (40.7%) had new palliative care referrals. Among 40 patients surveyed on their GOC discussion experience, 28 (70%) had discussions prior to treatment onset, 30 (75%) felt satisfied with the discussion timing, and 28 (70%) found GOC discussions beneficial. Conclusions: Among patients with advanced cancers, use of a documentation form for GOC documentation was associated with higher palliative care referral rates compared to cases when the form was not used. GOC discussions were met with overall satisfaction by patients. However, early documentation remained poor among oncologists despite implementation. Our study is limited by the single-center design, potential selection bias in patient surveys (40 respondents), and manual chart review errors. Future efforts will include electronic prompting and qualitative assessments of barriers among oncologists.
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 | 0,049 | 0,113 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».