A Technological Approach To Compensating for Cognitive Decline and Optimizing Healthcare Resources
Bibliographic record
Abstract
BACKGROUND: The Idem Clock, a smart connected clock created by Eugeria Inc., enables caregivers to schedule reminders remotely and receive notifications if reminders are not confirmed. Through the MEDTEQ+ Innovative Health Showcase Program, the Montreal West Island Integrated University Health and Social Services Centre tested the clock to evaluate its value in home care, specifically its potential to reduce health and social service assistants' visits for medication administration. The project also assessed secondary impacts on daily living activities and social isolation. METHOD: Over seven months, 48 older adults with mild to moderate cognitive impairments receiving home care services participated. Inclusion criteria included a Functional Autonomy Measurement System (FAMS) memory score of 0, -0.5, or -1, and a need for medication reminders. Exclusion criteria included severe memory impairment (FAMS score -2 or -3), Behavioral and Psychological Symptoms of Dementia (BPSD), or high-risk medication use. Participants were evaluated by a nurse, who confirmed eligibility, obtained consent, and demonstrated the clock to users and caregivers. Installed in users' homes, the clock displayed scheduled medication reminders. During the project, the nurse was responsible for scheduling medication reminders based on the participant's treatment. Nurses monitored compliance and received notifications when reminders were not confirmed. Performance was evaluated via feedback, re-evaluations, and daily home visits. RESULTS: Participants used the clock for an average of 66 days, with 81% continuing post-trial. During the trial, 6,365 home visits were avoided, achieving a ratio of 53 visits avoided per programmed reminder. Each clock displayed an average of 68 reminders monthly (mean of 2 per day), with users confirming 80% of them. Estimated cost savings totaled CAD 80,842 for the healthcare center. CONCLUSION: The Idem Clock shows strong potential to enhance home care by reducing resource utilization and promoting self-management for older adults with cognitive impairments. These findings support broader implementation, with recommended refinements to improve usability and application across diverse care settings.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".