COVID-19 – an opportunity to improve access to primary care through organizational innovations? A qualitative multiple case study in Quebec and Nova Scotia (Canada)
Bibliographic record
Abstract
BACKGROUND: COVID-19 catalyzed a rapid and substantial reorganization of primary care, accelerating the spread of existing strategies and fostering a proliferation of innovations. Access to primary care is an essential component of a healthcare system, particularly during a pandemic. We describe organizational innovations aiming to improve access to primary care and related contextual changes during the first 18 months of the COVID-19 pandemic in two Canadian provinces, Quebec and Nova Scotia. METHODS: We conducted a multiple case study based on 63 semi-structured interviews (n = 33 in Quebec, n = 30 in Nova Scotia) conducted between October 2020 and May 2021 and 71 documents from both jurisdictions. We recruited a diverse range of provincial and regional stakeholders (e.g., policy-makers, decision-makers, family physicians, nurses) involved in reorganizing primary care during the COVID-19 pandemic using purposeful sampling (e.g., based on role, region). Interviews were transcribed verbatim and thematic analysis was conducted in NVivo12. Emerging results were discussed by team members to identify salient themes and organized into logic models. RESULTS: We identified and analyzed six organizational innovations. Four of these - centralized public online booking systems, centralized access centers for unattached patients, interim primary care clinics for unattached patients, and a community connector to health and social services for older adults - pre-dated COVID-19 but were accelerated by the pandemic context. The remaining two innovations were created to specifically address pandemic-related needs: COVID-19 hotlines and COVID-dedicated primary healthcare clinics. Innovation spread and proliferation was influenced by several factors, such as a strengthened sense of community amongst providers, decreased patient demand at the beginning of the first wave, renewed policy and provider interest in population-wide access (versus attachment of patients only), suspended performance targets (e.g., continuity ≥80%) in Quebec, modality of care delivery, modified fee codes, and greater regional flexibility to implement tailored innovations. CONCLUSION: COVID-19 accelerated the uptake and creation of organizational innovations to potentially improve access to primary healthcare, removing, at least temporarily, certain longstanding barriers. Many stakeholders believed this reorganization would have positive impacts on access to primary care after the pandemic. Further studies should analyze the effectiveness and sustainability of innovations adapted, developed, and implemented during the COVID-19 pandemic.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".