An Integrated Approach to Stakeholder Engagement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Wait Time Information System (WTIS) project was a complex change-management initiative. For the first time in Ontario, wait time data would be captured directly from clinician offices and publicly reported in an effort to improve access to care. The change meant using new technology, new business processes and, most importantly, a new dimension of accountability for making improvements within the health system. Success required engaging thousands of individuals at all levels of healthcare, many of whom were skeptical and resistant to the upcoming change, and subsequently gaining their support and motivating them to use the WTIS and its data. To achieve the level of stakeholder engagement that would be required to deploy and sustain the WTIS, the project team needed to address both the business reasons for change, and the emotional reactions to it. The team applied a three-pronged approach encompassing strong communications, compelling adoption efforts and hands-on training. Communication focused on awareness and education, ensuring that information was coordinated, consistent and transparent. Adoption efforts involved helping hospitals and users understand and prepare for the impact of change. Training provided hands-on practice to get people comfortable with using the system. This article explores how information management/information technology (IM/IT) projects can integrate communications, adoption and training to drive stakeholder engagement. It also provides insight around how, when used effectively, these functions can maximize limited resources and provide valuable benefits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it