Bibliographic record
Abstract
Introduction: Integrating care is a developing feature of provincial health delivery in Canada for those with chronic conditions. The purposes of this project were to review the conceptual understandings underlying integrated care, examine the features of models of cost-effective care for the elderly, and then ascertain to what extent Canadian provinces were implementing these features.Method: These goals were accomplished through a review of the integrated care literature followed by a survey of the Canadian provinces. A pre-tested questionnaire was sent to each of the ten provincial Ministries of Health in 2008. The questionnaire collected basic background information and then asked a series of open- and close-ended questions about each of the best practice features of integrated care as found in the literature review.Results: System improvements in integrating care for the elderly are being implemented in Canadian provincial health care systems. There has been substantial improvement in the delivery of case management services but the supply of some community services could be improved. As well, the linkages amongst primary, acute and community care remain weak.Discussion and conclusion: Providing an adequate supply of services is an ongoing issue in many provinces and could be the result of either inadequate funding and/or poor targeting of scarce resources. While it is promising that so many provinces are starting to break down the silos amongst types of health care service providers, much remains to be accomplished. These issues are at the core of integrating care and are among the challenges being faced by other countries.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".