Telehealth challenges during COVID-19 as reported by primary healthcare physicians in Quebec and Massachusetts
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has driven primary healthcare (PHC) providers to use telehealth as an alternative to traditional face-to-face consultations. Providing telehealth that meets the needs of patients in a pandemic has presented many challenges for PHC providers. The aim of this study was to describe the positive and negative implications of using telehealth in one Canadian (Quebec) and one American (Massachusetts) PHC setting during the COVID-19 pandemic as reported by physicians. METHODS: We conducted 42 individual semi-structured video interviews with physicians in Quebec (N = 20) and Massachusetts (N = 22) in 2020. Topics covered included their practice history, changes brought by the COVID-19 pandemic, and the advantages and challenges of telehealth. An inductive and deductive thematic analysis was carried out to identify implications of delivering care via telehealth. RESULTS: Four key themes were identified, each with positive and negative implications: 1) access for patients; 2) efficiency of care delivery; 3) professional impacts; and 4) relational dimensions of care. For patients' access, positive implications referred to increased availability of services; negative implications involved barriers due to difficulties with access to and use of technologies. Positive implications for efficiency were related to improved follow-up care; negative implications involved difficulties in diagnosing in the absence of direct physical examination and non-verbal cues. For professional impacts, positive implications were related to flexibility (teleworking, more availability for patients) and reimbursement, while negative implications were related to technological limitations experienced by both patients and practitioners. For relational dimensions, positive implications included improved communication, as patients were more at ease at home, and the possibility of gathering information from what could be seen of the patient's environment; negative implications were related to concerns around maintaining the therapeutic relationship and changes in patients' engagement and expectations. CONCLUSION: Ensuring that health services provision meets patients' needs at all times calls for flexibility in care delivery modalities, role shifting to adapt to virtual care, sustained relationships with patients, and interprofessional collaboration. To succeed, these efforts require guidelines and training, as well as careful attention to technological barriers and interpersonal relationship needs.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".