Changes to telehealth practices in primary care in New Brunswick (Canada): A comparative study pre and during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: During the COVID-19 pandemic, telehealth technologies were used in the primary health care setting in New Brunswick as a means to continue providing care to patients while following public health guidelines. This study aimed to measure these changes and examine if they improved timely access to primary care. A secondary goal was to identify which telehealth technologies were deemed sustainable by primary care providers. METHODS: This was a comparative study on the use of telehealth technology before and during the COVID-19 pandemic. Between April 2020 and November 2020, 114 active primary care providers (family physicians or nurse practitioners) responded to the online survey. RESULTS: The findings illustrated an increase in the use of telehealth technologies. The use of phone consultations increased by 122%, from 43.9% pre-pandemic to 97.6% during the pandemic (p < 0.001). The use of virtual consultation (19.3% pre-pandemic vs. 41.2% during the pandemic, p < 0.001), emails and texts also increased during the pandemic. Whereas the more structural organizational tools (electronic medical charts and reservation systems) remained stable. However, those changes did not coincide with a significant improvement to timely access to care during the pandemic. Many participants (40.1%) wanted to keep phone consultations, and 21.9% of participants wanted to keep virtual consultations as part of their long-term practice. INTERPRETATION: The observed increase in the use of telehealth technologies may be sustainable, but it has not significantly improved timely access to primary care in New Brunswick.
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) | 0.000 | 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".