Assessing Risk among Frail Older Adults in Ontario, Canada, during the COVID-19 Pandemic: A Mixed Methods Evaluation of a Telephone Outreach Program
Bibliographic record
Abstract
We developed a pandemic telephone outreach protocol to identify risk for social isolation, health destabilization, medication issues, inadequate services and supports, and caregiver stress among older adults at high risk of destabilization. Screening, conducted between April 1, 2020, and May 8, 2020, was targeted to those who had previously been screened as frail or who were identified as vulnerable by their family physician. This study describes the implementation and results of this risk screening protocol and describes patient, caregiver, and health professional perceptions of this outreach initiative. Mixed methods included satisfaction surveys and interviews completed by patients/caregivers (N = 300 and N = 26, respectively) and health professionals (N = 18 and N = 9, respectively). A medical record audit collected information on patient characteristics and screening outcomes. A total of 335 patients were screened in the early weeks of the pandemic, of whom 23% were identified with at least one risk factor, most commonly related to the potential for health destabilization and medication risk. Follow-up referrals were made most frequently to physicians, a pharmacist, and a social worker. The outreach calls were very well received by patients and caregivers who described feeling cared for and valued at a time when they were socially isolated and lonely. The outreach calls provided access to trusted COVID-19 information and reassurance that health care was still available. The majority of health professionals (>86%) were “very” or “extremely” satisfied with the ease of completing the screening via telephone and value for time spent; for 79% the protocol was “very” or “extremely” feasible to implement. Health professional interviews revealed that patients were unaware they could access care during the pandemic lockdown but were reassured that care was available, potential crises were averted, and they supported future implementation. Risk screening provides a significant opportunity to provide information, support, and mitigate potential risks and is an important and feasible component of pandemic planning in primary care.
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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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".