Implementing the first regional hospice palliative care program in Ontario: the Champlain region as a case study
Bibliographic record
Abstract
BACKGROUND: Regionalization promotes planning and coordination of services across settings and providers to meet population needs. Despite the potential advantages of regionalization, no regional hospice palliative care program existed in Ontario, Canada, as of 2010. This paper describes the process and early results of the development of the first regional hospice palliative care program in Ontario. The various activities and processes undertaken and the formal agreements, policies and documents are described. METHODS: A participative approach, started in April 2009, was used. It brought together over 26 health service providers, including residential hospices, a palliative care unit, community and hospital specialist consultation teams, hospitals, community health and social service agencies (including nursing), individual health professionals, volunteers, patients and families. An extensive stakeholder and community vetting process was undertaken that included work groups (to explore key areas such as home care, the hospital sector, hospice and palliative care unit beds, provision of care in rural settings, e-health and education), a steering committee and input from over 320 individuals via e-mail and town-halls. A Transitional Leadership Group was elected to steer the implementation of the Regional Program over the summer of 2010. This group established the by-laws and details regarding the governance structure of the Regional Program, including its role, responsibilities, reporting structures and initial performance indicators that the Local Health Integration Network (LHIN) approved. RESULTS: The Regional Program was formally established in November 2010 with a competency-based Board of 14 elected members to oversee the program. Early work involved establishing standards and performance indicators for the different sectors and settings in the region, and identifying key clinical needs such as the establishment of more residential hospice capacity in Ottawa and a rural framework to ensure access for citizens in rural and remote regions. Challenges encountered are explored as are the process enablers and facilitators. The paper views the development and implementation process from the perspectives of several frameworks and models related to change management. CONCLUSIONS: Following on several initial achievements, the long term success of the Regional Program will depend on consolidating the early gains and demonstrating changes based on key measurable outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".