Altered cancer care delivery during COVID-19: Evaluating the impact of virtual clinics and treatment changes on oncology patient outcomes, quality of life, and satisfaction.
Bibliographic record
Abstract
e18618 Background: The coronavirus disease (COVID-19) pandemic has created unprecedented strain on healthcare systems across the world. COVID-19 has thought to have significant impacts on the oncology patient population and has affected their care. Additional research is needed to ascertain the impact of the COVID-19 pandemic at the patient level. We sought to evaluate whether the delivery of cancer care, quality of life (QoL) and treatment outcomes of oncology patients at Mount Sinai Hospital (MSH), Toronto, Canada was impacted by the COVID-19 pandemic. Methods: A 3-part longitudinal questionnaire study including 138 oncology patients receiving active treatment or in active follow-up at MSH was conducted between June 15, 2020 and August 25, 2021. The questionnaire consisted of the EORTC QLQ-C30 (European Organisation for Research and Treatment of Cancer QoL Questionnaire Version 3) and satisfaction with virtual healthcare questionnaire. The questionnaire was completed at baseline (Jun 15-Sep 8, 2020), 1 month follow-up (Jul 15-Oct 8, 2020), and 12 months follow-up (Aug 4-Aug 25, 2021). Repeated measures analysis of variance tests were performed to evaluate EORTC QLQ-C30 subscale score changes and satisfaction with virtual care question scores over time. Results: Overall, the mean EORTC QLQ-C30 QoL scores were seen to improve in oncology patients from 65.1 (SD±22.3) at baseline to 69.1 (SD±16.9) at 12 months follow-up (p = 0.2). Within the EORTC QLQ-C30 functional scales, mean role functioning and mean social functioning scores were observed to increase over 12 months of follow-up, 66.4 to 79.2 (p < 0.05) and 67.7 to 76.4 (p = 0.17), respectively. Little change was observed within other EORTC QLQ-C30 functional scales and individual symptom scales during follow-up. Over 12 months of follow-up, mean agreement (0 = strongly disagree to 6 = strongly agree) to the questionnaire statement regarding avoiding going to the hospital during COVID-19 pandemic had declined, from 4.6 (SD±2.0) at baseline to 3.9 (SD±2.2) at 12 months follow-up (p = 0.09). Although not significant, virtual care satisfaction generally decreased over the follow-up time period. 97% of 48 patients who completed the survey at 12 months of follow-up reported feeling more safe coming into the hospital when considering the current increased vaccination rates in Ontario. Conclusions: As the COVID-19 pandemic has evolved, there has been increased knowledge of disease transmission, along with the introduction of health care measures such as vaccination and treatment. During this time, cancer outpatients at MSH became more comfortable as demonstrated by improvements in both QoL and virtual care scores. Prospective studies should still be considered to assess the efficacy of different methods of improving oncology patient care and QoL during the COVID-19 pandemic.
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 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".