Mitigating the risk of COVID-19 in a large community oncology clinic and its impact on the patient experience.
Notice bibliographique
Résumé
e18631 Background: Cancer patients have a high risk of severe illness from COVID-19 infection, and the William Osler Health System oncology clinic (WOHS-OC) is in Brampton, ON, Canada, a COVID-19 hotspot with high community COVID-19 prevalence. As such, heightened symptom screening prior to entering the WOHS-OC, asymptomatic COVID-19 testing pre-chemotherapy, staff personal protective equipment (PPE) use, enhanced cleaning, and clinic capacity limits (including implementation of virtual visits) were employed in the outpatient WOHS-OC. This study examined patient's perspectives regarding the implemented containment and mitigation strategies in the WOHS-OC during the second wave of the COVID-19 pandemic. Methods: Consenting patients in the WOHS-OC from Dec 01 2020 to Feb 01 2021 were provided a written questionnaire regarding their care during the second wave of the COVID-19 pandemic. Questions about satisfaction with COVID-19 protocols were rated on an analogue scale from 1-5, with 1 being the worst and 5 being the best possible satisfaction. Patient demographics (age, sex, type of cancer, and treatment type) were obtained through electronic medical records. Patients also consented to a second survey should they contract COVID-19 regarding, symptoms and risk factors for contracting the virus. Results: Fifty-six patients with various solid and hematological malignancies consented to the study; median age 59.5, male (30%), type of treatment; chemotherapy (55%), immunotherapy (9%), targeted therapy (23%), biologic therapy (14%), endocrine therapy (11%). Patients felt safe coming to the oncology clinic (95% of respondents), and 100% of patients were screened for symptoms on entry. Prior to cancer treatment, 49% of participants were contacted to do a screening COVID-19 swab. In 57% of patients, at least one clinic visit was changed to virtual (telephone or video). Communication during virtual visits was felt to be adequate with 89% of patients rating communication 4 or 5. Rating of virtual visits compared to in-person visits was widely distributed (57% rated virtual 4 or 5 compared to in person). Infection control practices were rated highly (4 or 5; physical distancing 83%, enhanced cleaning 93%, staff screening 89%, and staff PPE 96%). No patients that consented to the survey contracted COVID-19 during the study period. Conclusions: COVID-19 mitigation strategies in the WOHS-OC made patients feel safe during the second wave of the pandemic. Additionally, despite high levels of community transmission, no patients responding to the survey tested positive for COVID-19 during the study period. Patients were satisfied with communication during virtual visits, however there was a wide distribution of follow-up preferences. Future interventions should be aimed at standardizing pre- treatment COVID-19 testing and delineating areas of virtual care that patients identify as needing improvement.
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 | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».