Bibliographic record
Abstract
Background: The Couchiching Ontario Health Team (OHT) partnership has spearheaded a significant system change to advance innovative and highly integrated population healthcare for unattached patients within our community. By addressing the needs of 20% of these individuals, the partnership has pioneered a novel care delivery method, marking an unprecedented achievement in our region's healthcare landscape.LearningsThe insights gained from our innovative model are intended to be shared broadly with patients, healthcare providers, and system innovators to enhance overall care delivery. These learnings underscore the importance of adapting new models to meet emerging healthcare needs.Partners InvolvedThe success of the Couchiching OHT Unattached Patient Care Model was bolstered by extensive support from a diverse array of partners. This collaborative effort included patient and family advisors, primary care providers, the Family Health Team, the Nurse Practitioner Led Clinic, emergency physicians and emergency department team members, hospitalists, community nurse practitioners, Ontario Health, municipal partners, local shelter partners, local universities, and the Orillia Soldiers' Memorial Hospital (OSMH).The InitiativeThe Couchiching OHT demonstrated remarkable passion and collaboration to transform COVID-9 care delivery into a more comprehensive healthcare innovation for unattached patients. Leveraging the robust centralized infrastructure established for the COVID-9 community response, the Couchiching OHT rebranded their efforts as the COHT Care Clinic. This clinic provided episodic primary care and served as an emergency room diversion, despite facing challenges related to healthcare human resources and provincial funding constraints.ResultsThe COHT Care Clinic has been recognized as a provincial model for episodic care for unattached patients, aligning with Ontario mandate to provide universal access to healthcare. Acknowledging the shortage of primary care providers in our community, the team developed a model that ensures access to care for all residents. This model triages patients for attachment based on acuity rather than a first-come, first-served basis from a central list. The effectiveness and dedication demonstrated by this model led to the successful funding proposal for the expansion of two primary care hubs in our community.LearningOur experience has yielded numerous valuable insights:Unattached care models are relatively new and challenging to implement, necessitating innovative approaches.Fee models in Ontario support various care delivery services; hence, partnership and integration across different teams are crucial for success.Understanding local care options and identifying gaps is vital for utilizing an unattached care pathway. This ensures that all patients experience warm transfers between care settings throughout their healthcare journey.Next StepsMoving forward, we will continue to seek opportunities to solidify unattached patient care pathways. Our goal is to ensure that the entire community retains access to care and to prioritize patient attachment based on acuity and equity-driven approaches rather than traditional first-come, first-served methods. By doing so, we aim to establish a more equitable and efficient system for patient rostering with clinicians, ensuring that all individuals receive the care they need in a timely manner.
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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 | 0.030 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.045 |
| Scholarly communication | 0.018 | 0.011 |
| Open science | 0.008 | 0.033 |
| Research integrity | 0.010 | 0.021 |
| Insufficient payload (model declined to judge) | 0.017 | 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".