Utilizing population-based clinical and administrative data to estimate the incremental healthcare costs of dementia and frailty among community-residing care recipients.
Bibliographic record
Abstract
IntroductionCurrent cost estimates for dementia in Canada are lacking and no studies have yet to examine the incremental healthcare costs associated with both dementia and frailty, despite evidence of increasing prevalence of both conditions and their bidirectional association. These data are essential for informed clinical and public policy programs.
 Objectives and ApproachUsing linked clinical and health administrative databases in Ontario, we conducted a cohort study of all long-stay home care clients aged 50+ years with a clinical assessment between April 2014 and March 2015 (n=160,209). We defined dementia using a validated algorithm, and frailty categories (robust, pre-frail, frail) using a modified frailty index from clinical assessment data. Clients were followed prospectively for 1-year, for which we obtained total- and sector-specific healthcare costs for all encounters. We calculated cost differences (in $2015CAD) between dementia-frailty groups using a survival- and covariate-adjusted cost estimator described by Manning and Basu (2010) that included dementia-frailty interactions.
 ResultsIn this population-based cohort of long-stay home care recipients, the prevalence of dementia was 26.8% and 33.3% of these clients were frail (vs. 26.9% among clients without dementia). Approximately 15% of the cohort died over the 1-year follow-up. The average 1-year estimated total health system cost was $26,965. On average, home care clients with dementia categorized as frail incurred $14,291 (SE=$139) more in charges than similar robust clients ($35,381 vs. $21,091, respectively). In contrast, frail persons without dementia incurred $12,796 (SE=$95) more in charges that similar robust clients ($33,659 vs. $20,864, respectively). Among frail persons, those with dementia incurred $1,722 (SE=$149) more in expenditures, on average. Wide variation in sector-specific costs were also observed by dementia and frailty strata.
 Conclusion/ImplicationsDementia and frailty pose significant challenges to healthcare systems. Our findings illustrate large incremental costs associated with frailty, regardless of dementia status. Further research using the linked clinical assessment and administrative data is needed to inform variations in, and to delineate key drivers of, formal healthcare and informal care costs associated with dementia and frailty.
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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 | 0.021 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".