Mending the Cracks: A Case Study in Using Technology to Assist with Transitional Care for Persons with Dementia
Bibliographic record
Abstract
Transitions between hospital and community are particularly challenging for vulnerable adults experiencing behavioural and psychological symptoms (BPSD) of dementia. Too often, miscommunication results in triggering a recurrence of disruptive behaviours leading to frustration of staff and families. As part of the implementation of Health Quality Ontario (HQO) Quality Standards, this project involved improving transitions using an electronic-based care plan on a 23-bed geriatric dementia unit in a mental health hospital. "My Dementia Careplan," is an interprofessional care plan that was developed in the electronic medical record (EMR) to enhance communication of information between healthcare providers when patients are being discharged to the community. It is written from the patient's perspective in collaboration with the family and interprofessional team. It describes strategies to manage behavioural challenges along with the standardized tools to objectively monitor progress. This care planning will help to support transition of knowledge between hospital and community.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".