Patient-reported experiences and outcomes of virtual care during COVID-19: a systematic review
Bibliographic record
Abstract
Abstract Introduction The onset of COVID-19 has caused an international upheaval of traditional in-person approaches to care delivery. Rapid system-level transitions to virtual care provision restrict the ability of healthcare professionals to evaluate care quality from the patient's perspective. This poses challenges to ensuring that patient-centered care is upheld within virtual environments. To address this, the study’s objective was to review how virtual care has impacted patient experiences and outcomes during COVID-19, through the use of patient-reported experience and outcome measures (PREMs and PROMs), respectively. Methods A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines to evaluate patient responsiveness to virtual care during COVID-19. Using an exhaustive search strategy, relevant peer-reviewed articles published between January 2020 and 2022 were pulled from MEDLINE, CINAHL, EMBASE, and PsychInfo databases. Study quality was independently assessed by two reviewers using the Mixed Methods Appraisal Tool. A patient partner was consulted throughout the study to provide feedback and co-conduct the review. Results After removing duplicates, 6048 articles underwent title and abstract review, from which 644 studies were included in the full-text review stage. Following this, 102 articles were included in the study. Studies were published in 20 different countries, were predominantly cross-sectional, and reported on the delivery of virtual care in specialized adult outpatient settings. This review identified 29 validated PREMs and 43 PROMs. Several advantages to virtual care were identified, with patients citing greater convenience, (such as saving travel time and cost, less waiting experienced to see care providers) and increased protection from viral spread. Some studies also reported challenges patients and caregivers faced with virtual care, including feeling rushed during the virtual care appointment, lack of physical contact or examination presenting barriers, difficulty with communicating symptoms, and technology issues. Conclusion This review provides supportive evidence of virtual care experiences during the COVID-19 pandemic from patient and caregiver perspectives. This research provides a comprehensive overview of what patient-reported measures can be used to record virtual care quality amid and following the pandemic. Further research into healthcare professionals’ perspectives would offer a supportive lens toward a strong person-centered healthcare system.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.072 | 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".