Impediments to Health Innovation in Canada: Identifying Policy Barriers in Alberta’s Precision Health Innovation and Commercialization Ecosystem
Bibliographic record
Abstract
Health systems globally are shifting towards precision health (PH), the utilization of individual information to inform health and social services delivery to improve health outcomes. PH is a major area of focus for economic development across the globe, however most Canadian provinces do not have a clear strategy for this sector. This research examines Alberta’s PH innovation and commercialization (I&C) ecosystem to identify key policy barriers in the development of new technologies and processes. An environmental scan of existing policies for PH through the lens of an innovation framework revealed three gaps in the PH I&C system. There is a lack of formal leadership, such as an I&C decision-making body; public policy development and implementation does not involve industry; and lastly, demand stimulating policies are absent or underrepresented. Qualitative semi-structured interviews were conducted to identify policy challenges utilizing perspectives from senior level executives currently engaged in PH I&C in Alberta. Participants were grouped by category from the Triple Helix Model of Innovation – Government, Industry and Academia. A qualitative thematic analysis of the interviews was conducted on the interview transcripts, coded using NVivo software, to generate thematic policy challenges. The findings from the interviews were grouped into five major policy challenges. Sub-optimal coordination between the various ecosystem players was the most consistent and prevalent findings across all groups. Most respondents identified the absence of a mandated organization for PH I&C as an impediment to decision-making. Multi-sectoral activity and collaboration were identified as concerns despite the importance of these activities in this sector. Tension between academics and government (including health service providers) was present between the research funding mechanisms “discovery-driven” versus “demand-pull”. Many respondents were concerned with the low level of local innovation public procurement by the health system. Findings suggest the need for a stronger role of governance structures to coordinate PH innovation ecosystem activity. A group with the capacity to address the multifaceted and interdisciplinary policy challenges may improve PH I&C outcomes in Alberta. Future research is required to inform design of horizontal and vertical governance structures.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.026 | 0.008 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".