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Record 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 on OpenAlexaffabout
Julie Lee, Harminder Singh, Kathleen Decker, Ramzi M. Helewa, Marylise Boutros, Jason Y. Park

Bibliographic record

VenueBritish journal of surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsUniversity of British ColumbiaMcGill UniversityCancerCare ManitobaUniversity of Manitoba
Fundersnot available
KeywordsMedicinePandemicCoronavirus disease 2019 (COVID-19)Cancer2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Cancer surgeryGeneral surgerySurgeryVirologyInternal medicineDiseaseInfectious disease (medical specialty)Outbreak

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.899
Threshold uncertainty score0.735

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0230.016
Scholarly communication0.0080.003
Open science0.0030.007
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.143
GPT teacher head0.433
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2022
Admission routes2
Has abstractyes

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