Cost-utility analysis of a multispecialty interprofessional team dementia care model in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVES: To examine the cost-effectiveness of Multi-specialty INterprofessional Team (MINT) Memory Clinic care in comparison to the provision of usual care. DESIGN: Using a Markov-based state transition model, we performed a cost-utility (costs and quality-adjusted life years, QALY) analysis of MINT Memory Clinic care and usual care not involving MINT Memory Clinics. SETTING: A primary care-based Memory Clinic in Ontario, Canada. PARTICIPANTS: The analysis included data from a sample of 229 patients assessed in the MINT Memory Clinic between January 2019 and January 2021. PRIMARY OUTCOME MEASURES: Effectiveness as measured in QALY, costs (in Canadian dollars) and the incremental cost-effectiveness ratio calculated as the incremental cost per QALY gained between MINT Memory Clinics versus usual care. RESULTS: MINT Memory Clinics were found to be less expensive ($C51 496 (95% Crl $C4806 to $C119 367) while slightly improving quality of life (+0.43 (95 Crl 0.01 to 1.24) QALY) compared with usual care. The probabilistic analysis showed that MINT Memory Clinics were the superior treatment compared with usual care 98% of the time. Variation in age was found to have the greatest impact on cost-effectiveness as patients may benefit from the MINT Memory Clinics more if they receive care beginning at a younger age. CONCLUSION: Multispecialty interprofessional memory clinic care is less costly and more effective compared with usual care and early access to care significantly reduces care costs over time. The results of this economic evaluation can inform decision-making and improvements to health system design, resource allocation and care experience for persons living with dementia. Specifically, widespread scaling of MINT Memory Clinics into existing primary care systems may assist with improving quality and access to memory care services while decreasing the growing economic and social burden of dementia.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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 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".