Mitigating the risk of COVID-19 in a large community oncology clinic and its impact on the patient experience.
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".