Ensuring the continuation of routine primary care during the COVID-19 pandemic: a review of the international literature
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has resulted in the diversion of health resources away from routine primary care delivery. This disruption of health services has necessitated new approaches to providing care to ensure continuity. OBJECTIVES: To summarize changes to the provision of routine primary care services during the pandemic. METHODS: Rapid literature review using PubMed/MEDLINE, SCOPUS, and Cochrane. Eligible studies were based in primary care and described practice-level changes in the provision of routine care in response to COVID-19. Relevant data addressing changes to routine primary care delivery, impact on primary care functions and challenges experienced in adjusting to new approaches to providing care, were obtained from included studies. A narrative summary was guided by Burns et al.'s framework for primary care provision in disasters. RESULTS: Seventeen of 1,699 identified papers were included. Studies reported on telehealth use and public health measures to maintain safe access to routine primary care, including providing COVID-19 screening, and establishing dedicated care pathways for non-COVID and COVID-related issues. Acute and urgent care were prioritized, causing disruptions to chronic disease management and preventive care. Challenges included telehealth use including disparities in access and practical difficulties in assessing patients, personal protective equipment shortages, and financial solvency of medical practices. CONCLUSIONS: Substantial disruptions to routine primary care occurred due to the COVID-19 pandemic. Primary care practices' rapid adaptation, often with limited resources and support, demonstrates agility and innovative capacity. Findings underscore the need for timely guidance and support from authorities to optimize the provision of comprehensive routine care during pandemics.
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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 | 0.010 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.023 | 0.027 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".