A Disease Management Approach to Health Technology Assessment: A Multi-Methods Analysis for the Prevention and Management of Clostridioides difficile Infection
Bibliographic record
Abstract
Health technology assessment (HTA) is a multidisciplinary process with a primary goal to inform health system decision-making. HTA is considered the reference paradigm for the assessment of technology in healthcare with efforts to achieve a high-quality health system. HTA conventionally responds to questions about new market entrants for a single decision-maker. In the context of Canada’s decentralized health system, many decision-makers means many, typically narrow, scopes of analysis. Literature suggests that there are likely implications of this environment which may include overlooking opportunities to identify an optimal mix of interventions that maximizes health outcomes. Our work aimed to draw attention to the conventional scope of the decision problem in HTA, and explore one alternative to this conventional approach, a disease management approach.Study 1 used scoping review methodology to assess how, and to what extent, a systems-level perspective is considered in decision-making for the adoption or de-adoption of a health intervention or technology (e.g., drug, medical device, procedure). Study 2 was a second scoping review to assess how the scope of the decision problem is typically defined within one component of HTA, economic evaluation, and specifically for Clostridioides difficile (C. difficile) infection interventions. Study 3 used economic evaluation methodology, and C. difficile as an exemplar, to identify the optimal implementation strategy for a new vaccine in combination with a new (more effective, more costly) treatment (disease management approach) compared to the conventional approach which typically assesses interventions independently. Study 4 used qualitative methodology to explore opportunities for conceptualizing the decision space in HTA as a disease management approach versus an intervention management approach. Our research confirmed that intervention assessments are typically conducted in isolation to other interventions, assuming that the surrounding intervention environment is static. We highlight that an expanded approach to how we structure the decision problem in HTA, a disease management approach, will not be without its challenges. We provide quantitative and qualitative evidence in support of a step toward a more system-level perspective to HTA and endeavor to showcase a potential opportunity for HTA to contribute to a more proactive, resilient, and sustainable healthcare system in Canada.
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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 | 0.178 | 0.246 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.018 |
| Bibliometrics | 0.023 | 0.015 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".