Protocol for an economic evaluation of scalable strategies to improve mental health among perinatal women: non-specialist care delivered via telemedicine vs. specialist care delivered in-person
Bibliographic record
Abstract
BACKGROUND: Perinatal depression affects an estimated 1 in 5 women in North America during the perinatal period, with annualized lifetime costs estimated at $20.6 billion CAD in Canada and over $45.9 billion USD in the US. Access to psychological treatments remains limited for most perinatal women suffering from depression and anxiety. Some barriers to effective care can be addressed through task-sharing to non-specialist providers and through telemedicine platforms. The cost-effectiveness of these strategies compared to traditional specialist and in-person models remains unknown. This protocol describes an economic evaluation of non-specialist providers and telemedicine, in comparison to specialist providers and in-person sessions within the ongoing Scaling Up Maternal Mental healthcare by Increasing access to Treatment (SUMMIT) trial. METHODS: The economic evaluation will be undertaken alongside the SUMMIT trial. SUMMIT is a pragmatic, randomized, non-inferiority trial across five North American study sites (N = 1,226) of the comparable effectiveness of two types of providers (specialist vs. non-specialist) and delivery modes (telemedicine vs. in-person) of a behavioural activation treatment for perinatal depressive and anxiety symptoms. The primary economic evaluation will be a cost-utility analysis. The outcome will be the incremental cost-effectiveness ratio, which will be expressed as the additional cost required to achieve an additional quality-adjusted life-year, as assessed by the EuroQol 5-Dimension 5-Level instrument. A secondary cost-effectiveness analysis will use participants' depressive symptom scores. A micro-costing analysis will be conducted to estimate the resources/costs required to implement and sustain the interventions; healthcare resource utilization will be captured via self-report. Data will be pooled and analysed using uniform price and utility weights to determine cost-utility across all trial sites. Secondary country-specific cost-utility and cost-effectiveness analyses will also be completed. Sensitivity analyses will be conducted, and cost-effectiveness acceptability-curves will be generated, in all instances. DISCUSSION: Results of this study are expected to inform key decisions related to dissemination and scale up of evidence-based psychological interventions in Canada, the US, and possibly worldwide. There is potential impact on real-world practice by informing decision makers of the long-term savings to the larger healthcare setting in services to support perinatal women with common mental health conditions.
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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 | 0.067 | 0.128 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.230 | 0.034 |
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".