Importance of broad, equity-based approach to community engagement in supporting Ontario Health Teams and redesigning integrated care delivery
Bibliographic record
Abstract
Ontario Health Teams (OHTs) are a model of integrated care(IC) where primary care, hospitals, long-term care, home care, and social services work together with patient/caregiver advisors as one coordinated team. Our population health management focus requires that patients/caregivers and community members are recognized and supported as partners, and included in decision-making for redesigning integrated care delivery. An example of ETHP’s commitment to involving the community is the creation of a network of engaged patient/caregiver and community advisors to support our OHT and its partner organizations. Our Community Advisory Council (CAC) started in 2019 as a small group of five patients/caregivers who were brought together to help with the development of our OHT application. The small group of five quickly grew to 15 in our first year as OHT. As we sought to implement a broader community engagement approach, we shifted our recruitment focus to ETHP’s priority neighbourhoods and equity-deserving communities. We now have a community network of 60 active patient/caregiver advisors and 60 community health ambassadors supporting our IC work. Our engagement strategy focuses on involving patient and caregiver advisors in strategic planning and service co-design. Having supportive leadership and accountability has enabled our success. Our leadership team proactively identifies opportunities to involve the community in all aspects of our work. We try to incorporate patient/caregiver input in multiple ways, including interviews, surveys, and focus groups. However, we see the most value in involving patients/caregivers in ETHP committees’s work and creating dedicated advisory councils. Using this approach to engagement, we have created five additional advisory councils – two councils in the Thorncliffe Park and Taylor Massey priority neighbourhoods, a caregiver advisory group, and two youth advisory councils. Dedicated community advisory bodies comprised of members who are representative of the community provide a platform for a broader, more diverse range of perspectives. This approach to engagement (working at the Empowerment end of the engagement spectrum) has also resulted in various community-led initiatives. Our ETHP’s biannual planning sessions are proudly hosted by the community. The last session in July 2023 drew 160 participants, more than 40 of whom were community members. Similarly, in one of our workstreams, ETHP’s caregiver advisory group co-designed a series of 20 animated instructional videos (https://www.woodgreen.org/caregivers) to help patients and caregivers navigate the healthcare system. These are some examples of the successful partnership between ETHP and our patient/caregiver advisors. Having robust engagement is particularly important for IC models like the OHTs which are tasked with meeting the needs of a broader population. Since its inception, ETHP’s advisory network is increasingly recognized as a resource for ETHP and its many partner organizations. The streamlined engagement processes and the ease of access to this large and diverse network of advisors have enabled ETHP to improve its delivery of programs and services to meet the needs of our East Toronto community. This work would not be possible without the dedication of our committed advisors who collectively contribute numerous volunteer hours of their time to bring to the table the patient/caregiver voice.
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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 | 0.051 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.017 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".