Examining virtual visit use during a pandemic and perspectives of primary care providers, patients and caregivers: a mixed-methods research protocol
Bibliographic record
Abstract
Introduction COVID-19 prompted rapid shifts to virtual primary care; however, the secondary implications and ideal applications of this change require further consideration. Patient and public stakeholder input has been bypassed. To integrate virtual care (VC) in what currently appears to be a lengthier battle against COVID-19 and related sequelae, further investigation is needed to support ideal implementation and use. This study aims to describe factors associated with the use of virtual visits in primary care practices, along with more in-depth description of users’ experiences and perspectives. Methods and analysis This study will be conducted in three phases, using a mixed-methods approach and in consultation with community advisors. Phase 1 will analyse data from electronic medical records (EMRs) to characterise the use and users of VC in primary care during the early phase of the COVID-19 pandemic. Analysis will be primarily descriptive; regression modelling will assess associations between patient and provider factors with a virtual visit. In phase 2, we will use an EMR-facilitated process to automate the distribution of patient surveys within an estimated 10 clinics. These surveys aim to describe care experiences, transactional use and perspectives of VC. In phase 3, focus groups with patients, caregivers and primary care clinicians will seek more in-depth exploration of VC regarding accessibility of care, acceptability and perceptions of quality care. Interpretive phenomenological analysis will be used for thematic analysis. The framework method will employ a matrix structure to organise the data and to facilitate comparison, integration and further interpretation. Ethics and dissemination This study has been approved by the University of Manitoba’s Health Research Ethics Board (HS24197). A co-designed dissemination strategy will include reports and infographics to policymakers and the public, manuscripts and presentations to academic and clinician audiences, and contributions to a learning plan for professional development.
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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 | 0.099 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.033 | 0.008 |
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".