Abstract 3468: Emerging lessons from patient-reported hospital discharge experiences among hospitalized cancer patients with frequent emergency department use
Notice bibliographique
Résumé
Abstract Background: While teamwork is essential to providing high-quality patient-centered care, challenges in interprofessional collaboration and decision-making in the hospital settings are common, especially for cancer patients. The purpose of this study was to identify emerging themes related to hospital discharge experiences among patients hospitalized for cancer who became frequent emergency department (ED) users following their hospital discharge. Design & Methods: A cohort of cancer patients discharged from an academic health center in Montreal (Canada) between October 2014 and November 2016 was assembled. Frequent ED (FED) users were identified as patients who had a > 4 ED visits in the year following hospital discharge using health administrative claims from the provincial universal health care program. Qualitative analysis of telephone interviews conducted with patients 30 days’ post-discharge were used for in-depth exploratory analyses to characterize hospital discharge experiences and transition process from the hospital to the community. Results: A cohort of 1253 cancer patients was formed. The mean age was 70.9 (SD=11.8) and the most frequent cancers included 488 (38.9%) respiratory and 309 (24.6%) upper digestive cancer. Overall, 14.5% (n=182) of patients became FED users. Content analyses revealed the most common emerging themes from the FED patients interviews on hospital discharge experiences. These included:1. Early hospital discharge putting patients at high risk of being re-admitted and going back to the ER shortly after that. Some patients mentioned post-discharge complications and emerging of new health issues that could have been avoided if patient was kept in the hospital for longer.2. Lack of communication between different specialists at the hospital. Some patients mentioned the help of a nurse as crucial during inpatient stays in maintaining communication between doctors. 3. Lack of communication of medications prescribed. Some patients mentioned the lack of communication of what doses was modified, what medications were stopped and which ones were newly prescribed.4. The need to schedule follow-up appointments at the time of hospital discharge. This becomes especially important for vulnerable patients who have been on pain medication during the hospital stay, affecting their cognitive abilities and making post-discharge planning more difficult. Conclusions: This study using integrated data from administrative claims and patient interviews provided insights into the challenges related to hospital discharge experiences and transition into community among hospitalized cancer patients with frequent emergency department use. Application of our findings could assist in hospital discharge preparation and improvement in healthcare delivery and health outcomes. Citation Format: Siyana Kurteva, Robyn Tamblyn. Emerging lessons from patient-reported hospital discharge experiences among hospitalized cancer patients with frequent emergency department use [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3468.
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 | 0,004 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».