COVID-19's Perceived Impact on Primary Care in New England: A Qualitative Study
Bibliographic record
Abstract
BACKGROUND: COVID-19 impacted primary care delivery, as clinicians and practices implemented changes to respond to the pandemic while safely caring for patients. This study aimed to understand clinicians' perceptions of the positive and negative impacts of COVID-19 on primary care in New England. METHODS: This qualitative interview study was conducted from October through December 2020. Participants included 22 physicians and 2 nurse practitioners practicing primary care in New England. Data were thematically coded and analyzed deductively and inductively using content analysis. RESULTS: Through qualitative content analysis, 4 areas were identified in which clinicians perceived that COVID-19 impacted primary care: 1) bureaucracy, 2) leadership, 3) telemedicine and patient care, and 4) clinician work-life. Our findings suggest that the positive impacts of COVID-19 included changes in primary care delivery, new leadership opportunities for clinicians, flexible access to care for patients via telemedicine, and a better work-life balance for clinicians. Respondents identified negative impacts related to sustaining pandemic-inspired changes, the inability for some populations to access care via telemedicine, and the rapid implementation of telemedicine causing frustration for clinicians. CONCLUSIONS: Understanding clinician perspectives on how primary care transformed to respond to COVID-19 helps to identify beneficial pandemic-related changes that should be sustained and ideas for improvement that will support patient care and clinician engagement.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".