Understanding the benefits and challenges of outpatient virtual care during the COVID-19 pandemic in a Canadian pediatric rehabilitation hospital
Bibliographic record
Abstract
The evolving virtual health care experience highlights the potential of technology to serve as a way to enhance care. Having virtual options for assessment, consultation and intervention were essential during the coronavirus (COVID-19) pandemic, especially for children with disabilities and their families. The purpose of our study was to describe the benefits and challenges of outpatient virtual care during the pandemic within pediatric rehabilitation. This qualitative study, part of a larger mixed methods project, involved in-depth interviews with 17 participants (10 parents, 2 youth, 5 clinicians) from a Canadian pediatric rehabilitation hospital. We analyzed the data using a thematic approach. Our findings demonstrated three main themes: (1) benefits of virtual care (e.g., continuity of care, convenience, stress reduction and flexibility, and comfort within the home environment and enhanced rapport); (2) challenges related to virtual care (e.g., technical difficulties and lack of technology, environmental distractions and constraints, communication difficulty, and health impacts); and (3) advice for the future of virtual care (i.e., offering choice to families, enhanced communication and addressing health equity issues). Clinicians and hospital leaders should consider addressing the modifiable barriers in accessing and delivering virtual care to optimize its effectiveness. Families are invested in access to virtual care appointments and can benefit from clear communication about choices regarding appointment options and supports in how to access and use technology for equitable access to care.Hospitals should aim to provide clinicians with an appropriate workspace (i.e., private, quiet with adequate room to demonstrate what they need to do), equipment and technology to have virtual care appointments.Current understanding of virtual care delivery suggests a tailored approach, with some types of appointments, such as follow-ups or check-ins, more suited to this modality than other more hands-on therapy. Families are invested in access to virtual care appointments and can benefit from clear communication about choices regarding appointment options and supports in how to access and use technology for equitable access to care. Hospitals should aim to provide clinicians with an appropriate workspace (i.e., private, quiet with adequate room to demonstrate what they need to do), equipment and technology to have virtual care appointments. Current understanding of virtual care delivery suggests a tailored approach, with some types of appointments, such as follow-ups or check-ins, more suited to this modality than other more hands-on therapy.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".