Transforming Health through Integrated Care. A Canadian collective research platform.
Bibliographic record
Abstract
The Canadian Institutes of Health Research (CIHR) launched a strategic research funding program called Transforming Health with Integrated Care (THINC). This initiative is a bold step forward to address the very complex challenges associated with implementing and sustaining integrated care at scale. Upwards of 100 grants have been funded to contribute to the knowledge base and the application of knowledge to improve patient and caregiver experience, provider experience, health outcomes and costs while considering and addressing health equity (Quintuple Aim). The flagship program of the THINC initiative includes 13 Implementation Science Teams (ISTs), each funded with $2 Million (CAD) over 5 years and a Knowledge Mobilization (KM) hub, which is being coordinated through the International Foundation for Integrated Care (IFIC) Canada Country Hub. There are several key principles and foundations for the THINC program. Each funded program requires quadripartite leadership including Researcher, Decision-Maker, Provider and Patient/Caregiver co-leadership. Each grant also requires both a Sex and Gender and an Equity champion to ensure attention to these critical perspectives in the programs. In this workshop we will engage in discussion about co-designing research and programs with such quadripartite leadership to: 1) ensure that the research is relevant and used for health care delivery planning by decision-makers; and 2) ensure that the research is relevant to front line health care providers and to patients and caregivers. We will also have discussion about how Implementation Science research in particular can benefit from the multi-stakeholder leadership. In this workshop we will introduce the overall CIHR program, as well as five of the THINC ISTs and the KM hub led by IFIC Canada. Small-group round-table discussions amongst workshop participants (researchers, providers, decision-makers and patients) will share international experience with, and reactions to this type of collaboration. There will be 3 key topics for discussions: First will focus on the representation of the four types of roles included as leaders in each of the projects including how these individuals are identified and how their input is recognized and included in project decision-making. Second will be the challenges and opportunities that can be generated through Implementation Science research. And third will be recommendations for design elements for collaborative research and evaluation that can support scale and spread of integrated care. The small-group round-table discussion will be facilitated and recorded by team leads from the ISTs. Summative insights from the discussions and key recommendations will be identified and summarized. This workshop will be of tremendous value to all types of stakeholders to develop common understanding towards approaching integrated care research and evaluation using this quadripartite and implementation science approach. Timing: The timing of the program is to spend 20 minutes outlining the overall key design elements (5 minutes) and providing the examples of the 5 participating research teams (3 minutes each). Then the three discussion topics will be given 15 minutes each. There will then be 15 minutes for report-back and summary from all of the breakout groups and 10 minutes for session synthesis and final comments/questions.
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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 | 0.045 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".