Organizational implications of implementing a new adverse drug event reporting system for care providers and integrating it with provincial health information systems
Bibliographic record
Abstract
Cross-sector collaborations between academia, government, and private industry, known as Triple Helix configurations, are increasingly common. In the health Information Technology (IT) sector, such configurations often also include health delivery organizations where technology is implemented and used. The complexity of collaborating within and between multiple organizations can present hurdles for innovators that are seldom discussed in the literature. We outline challenges we encountered in cross-sector collaboration and offer some guiding principles for decision-makers, academics, industry partners, and health delivery organizations to successfully negotiate divergent approaches to innovation and implementation. We discuss an innovative project that aims to implement a researcher-designed adverse drug event reporting system into clinical care and integrate it with provincial and health authority IT systems. Based on our experience, implementing an interoperable health IT system must extend beyond technical integration to encompass meaningful stakeholder engagement to ensure utility for end-users and beneficial impact for participating organizations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".