Understanding the experience of clinicians and non-clinical staff in Integrated Virtual Care, a hybrid primary care program in rural Ontario, Canada: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Current physician shortages are exacerbated in rural areas, worsening access to primary care. In Renfrew County, Ontario, the Integrated Virtual Care (IVC) program addresses this by attaching patients to a family physician working predominantly off-site, supported by an interprofessional healthcare team at a local clinic. Patients receive a hybrid of in-person and virtual care, based on their individual clinical needs and preferences. Limited evidence exists regarding the experiences of clinicians and non-clinical staff working in hybrid teams, with some members working off-site. This study explored the experiences of family physicians, interprofessional health providers (IHP), and non-clinical staff (clerical staff, managers, and leaders) working in a hybrid primary care program. METHODS: We conducted a qualitative descriptive study using one-on-one semi-structured interviews with clinicians (physicians and interprofessional team) and non-clinical staff working in the IVC program. Interview questions addressed satisfaction, team communication, collaboration, technology use, and rapport with patients. Transcripts were analyzed thematically using an inductive approach. Themes and quotes were then charted by participant type: physician, interprofessional health provider (IHP), and non-clinical staff. RESULTS: Sixteen participants (10 clinicians and six non-clinical staff) were interviewed. Five themes were generated, describing their experiences within the IVC program: support for IVC and meeting community needs, importance and role of interprofessional and non-clinical teams, IVC as a developing model: early program experiences, ongoing logistical challenges, and varied views on strengths and benefits. After charting themes by participant type, we identified a number of diverging views among the three groups, with perceived program benefits being more pronounced for physicians. CONCLUSIONS: Understanding the experiences of clinicians and non-clinical staff, which emphasized community ties, roles of clinical and non-clinical teams, and supportive leadership environments, can inform improvements to programs that combine interprofessional primary care teams and virtual technologies to enhance access to primary care in rural areas.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".