Changes In Primary Care Of Older Adults Since COVID-19
Bibliographic record
Abstract
Purpose: With the start of the SARS-COV-2 pandemic in March 2020, Canadian primary care practices temporarily shifted from in-person to virtual care. The purpose of this thesis was to understand whether the pandemic impacted the primary care management of older adults with varying levels of frailty and multimorbidity in terms of care modality, volume of encounters, and visits for anxiety/depression. It also aimed to identify which patients comparatively experienced greater reductions in frequencies of routine preventive care and monitoring activities. Methods: A research database from a sub-set of MUSIC family practice for patients ≥ 65 years of age (n=1813) was employed. Patient demographics, clinician-assessed frailty status, encounters, and chronic disease management information were retrieved. Changes from 14 months pre to 14 months since (peri) the pandemic were described and associations between patient characteristics and the extent of changes in outcomes from pre- to peri-pandemic were analyzed using regression models. Results: The mean age was 74 years, with a mean of 2.5 chronic conditions (26% hypertension, 14% diabetes). 2.1% of patients experienced high frailty levels. The mean number of encounters increased peri-pandemic overall (peri: 10.4 (SD 11.1) vs. pre: 7.1 (SD 5.5)) and for anxiety/depression, with most visits becoming virtual. Increasing numbers of overall visits were significantly associated with female sex, increasing frailty level, and having 4+ conditions. While the frequency of routine preventive and monitoring activities related to chronic conditions decreased, the mean values (e.g., lab results) did not considerably change. In the adjusted models, generally older patients, with increasing levels of frailty, and numbers of conditions tended to receive more care, however most associations were not statistically significant. Conclusion: Overall encounters and visits related to anxiety/depression increased peri-pandemic. Despite concerns about pandemic-related care disruptions, common elements of primary care among higher risk older patients were not notably impacted.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".