What are COVID-19 Patient Preferences for and Experiences with Virtual Care? Findings From a Scoping Review
Bibliographic record
Abstract
Virtual care became a routine method for healthcare delivery during the coronavirus disease 2019 (COVID-19) pandemic. Patient preferences are central to delivering patient-centered and high-quality care. The pandemic challenged healthcare organizations and providers to quickly deliver safe healthcare to COVID-19 patients. This resulted in varied implementation of virtual healthcare services. With an increased focus on remote COVID-19 monitoring, little research has examined patient experiences with virtual care. This scoping review examined patient experiences and preferences with virtual care among community-based self-isolating COVID-19 patients. We identified a paucity of literature related to patient experiences and preferences regarding virtual care. Few articles focused on patient experiences and preferences as a primary outcome. Our research suggests that (1) patients view virtual care positively and to be feasible to use; (2) patient access to technology impacts patient satisfaction and experiences; and (3) to enhance the patient experience, healthcare organizations and providers need to support patient use of technology and resolve technology-related issues. When planning virtual care modalities, purposeful consideration of patient experiences and preferences is needed to deliver quality patient-centered care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".