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Enregistrement W4283574635 · doi:10.1093/bjs/znac227

Cancer surgery in Canada during the COVID-19 pandemic: qualitative analysis of cancer surgeons’ perspectives

2022· article· en· W4283574635 sur OpenAlexaffabout
Julie Lee, Harminder Singh, Kathleen Decker, Ramzi M. Helewa, Marylise Boutros, Jason Y. Park

Notice bibliographique

RevueBritish journal of surgery · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueCOVID-19 and healthcare impacts
Établissements canadiensUniversity of British ColumbiaMcGill UniversityCancerCare ManitobaUniversity of Manitoba
Organismes subventionnairesnon disponible
Mots-clésMedicinePandemicCoronavirus disease 2019 (COVID-19)Cancer2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Cancer surgeryGeneral surgerySurgeryVirologyInternal medicineDiseaseInfectious disease (medical specialty)Outbreak

Résumé

récupéré en direct d'OpenAlex

Dear Editor The coronavirus disease 2019 (COVID-19) pandemic has presented unprecedented challenges to healthcare systems worldwide. In Canada, provinces and jurisdictions implemented directives to preserve and redirect resources, including reducing or cancelling non-emergency surgical procedures, which affected cancer treatments1–3. How these changes were enacted at the practitioner level by cancer surgeons directly engaged with patients has received little attention. The authors undertook a qualitative study to assess cancer surgeons’ perspectives on cancer treatment and the challenges they faced during the COVID-19 pandemic. Semistructured telephone interviews were conducted with 11 colorectal and gastric cancer surgeons from across Canada during the first wave of the pandemic (June 2020) (Fig. S1 and Table S1). Two researchers analysed the data for emergent themes using a grounded theory approach4,5. The data were organized using NVivo™ 12 software (QSR International, Melbourne, Victoria, Australia). Four major themes emerged from this analysis of surgeons’ perspectives on cancer surgery during the pandemic: surgical processes, surgeon stress, infection control, and cancer outcomes. The surgical processes and surgeon stress themes are discussed below (Table 1). The infection control and cancer outcomes themes are outlined in Tables S2 and S3. Summary of surgical processes and surgeon stress themes and subthemes with exemplar quotations OR, operating room. Summary of surgical processes and surgeon stress themes and subthemes with exemplar quotations OR, operating room. The surgical processes theme described the factors involved in performing cancer surgery during the pandemic. It was organized into the following subthemes: referral volumes, prioritization process, operative cases, treatment alterations, communication with leadership, unpredictable schedules, and surgical backlog. Participants reported receiving fewer cancer referrals, which they attributed to patients’ reluctance to seek healthcare services, difficulties in accessing care from primary or specialty physicians owing to reduced office capacity or pandemic-related office closures, and reductions in screening activities and diagnostic services (such as CT and endoscopy). They further described decreased operating room (OR) access because of institutionally or regionally mandated OR slate reductions or closures, although the degree of reductions varied by region and course of the pandemic. Many institutions set up prioritization processes to prioritize operative cases for the limited number of OR slates available, but the organization and transparency of these processes were variable. Most participants perceived delays in cancer operations because of OR reductions, especially for less urgent or earlier-stage cancers. Finally, participants were concerned about a potential surgical backlog of patients awaiting diagnosis and treatment of cancer, and their institutions’ preparedness to manage patient volumes once the pandemic had slowed down. Participants expressed heightened stress levels during the pandemic related to their role as surgeons and in their personal lives. The two major professional stressors were increased workloads and dealing with the uncertainty of whether OR requests would be approved. The process of seeking approval for surgery required increased administrative work. Surgeons were also unable to plan their schedules ahead of time and instead were constantly on standby, waiting to find out whether cases were approved and then needing to clear their schedules when OR time became available. Uncertainty in participants’ ability to provide timely care for their patients also caused stress. Participants also experienced pandemic-related stress in their personal lives, including concerns about their own health, managing childcare with schools closed, and financial concerns in the event of a prolonged OR shutdown. This study has highlighted areas requiring urgent attention to minimize negative and ongoing effects on patients with cancer, including diagnostic delays, developing reasonable and manageable prioritization processes a priori, dealing with backlogs of patients needing cancer treatments, and ongoing physician stress and burnout. Such studies need to be performed on an ongoing basis to mitigate negative unintended impacts on non-pandemic-related care and plan for future waves/pandemics. The authors have no funding to declare. Disclosure. The authors declare no conflict of interest. Supplementary material is available at BJS online.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,018
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,899
Score d'incertitude au seuil0,735

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0090,018
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,005
Études des sciences et des technologies0,0230,016
Communication savante0,0080,003
Science ouverte0,0030,007
Intégrité de la recherche0,0020,007
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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.

Tête enseignante Opus0,143
Tête enseignante GPT0,433
Écart entre enseignants0,290 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2022
Routes d'admission2
Résumé présentoui

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