Program Evaluation of SeeMe™: Understanding Frailty Together
Bibliographic record
Abstract
Background: (www.perleyhealth.ca), a comprehensive approach to care that integrates the assessment and management of frailty, with an emphasis on goals of care planning. Methods: Program evaluation over the first year of SeeMe™ used a mixed-methods approach involving quantitative data from surveys, goals of care preferences, hospital transfers, and qualitative data from interviews. Results: The SeeMe™ training is an effective way to educate nurses and physicians in long-term care about frailty. For residents with documented care preferences prior to SeeMe™, there was a 15% reduction in the number of residents who preferred to be transferred to hospital post-SeeMe™ implementation. There was no significant decrease in hospital transfers during the first year the program was introduced. Conclusion: After the roll-out of SeeMe™, nurses, physicians, and families reported high satisfaction with the program, and nurses reported an increase in knowledge and confidence. There was also a reduction in the number of residents and families selecting to transfer to hospital. This suggests that the education from SeeMe™ influenced residents and families to choose less invasive interventions in the context of frailty and quality of life goals.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".