Building a Comprehensive System of Services to Support Adults Living with Long-Term Mechanical Ventilation
Bibliographic record
Abstract
Background. Increasing numbers of individuals require long-term mechanical ventilation (LTMV) in the community. In the South West Local Health Integration Network (LHIN) in Ontario, multiple organizations have come together to design, build, and operate a system to serve adults living with LTMV. Objective. The goal was to develop an integrated approach to meet the health and supportive care needs of adults living with LTMV. Methods. The project was undertaken in three phases: System Design, Implementation Planning, and Implementation. Results. There are both qualitative and quantitative evidences that a multiorganizational system of care is now operational and functioning in a way that previously did not exist. An Oversight Committee and an Operations Management Committee currently support the system of services. A Memorandum of Understanding has been signed by the participating organizations. There is case-based evidence that hospital admissions are being avoided, transitions in care are being thoughtfully planned and executed collaboratively among service providers, and new roles and responsibilities are being accepted within the overall system of care. Conclusion. Addressing the complex and variable needs of adults living with LTMV requires a systems response involving the full continuum of care.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".