Predictors of Home Care Costs Among Persons With Dementia, Amyotrophic Lateral Sclerosis, and Multiple Sclerosis in Ontario
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Home care is an important service for persons with neurological conditions, but little is known about factors affecting health care costs in this setting. Using administrative data collected with the Resident Assessment Instrument for Home Care (RAI-HC), this study identified factors associated with home care costs for recipients of home care services with Alzheimer disease or related dementias, multiple sclerosis, and/or amyotrophic lateral sclerosis. As part of this study, the effectiveness of the Resource Utilization Groups for Home Care (RUG-III/HC), a case-mix classification system developed for the RAI-HC, in predicting care costs for this population, was also tested. Clinical characteristics indicative of greater disease severity had high levels of significance in predicting home care costs. In particular, the RUG-III/HC was highly predictive of home care costs for 3 neurological conditions, indicating the validity of this case-mix system for this population. With the increasing prevalence of neurological conditions and demand for home care services, future studies should continue to focus on identifying specific predictors care costs for those with neurological conditions in this care setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it