Bibliographic record
Abstract
Introduction: The volunteer (third) sector provides double the care in the community than does the healthcare system. However, within the geographic jurisdictions that a health system operates, there may be thousands of third sector organizations. In order to best meet individual and population medical and social needs, care provided by the third sector needs to be integrated with health system care. This can be challenging given the complexity of a health care system and the number of third sector organizations. The process by which the province of Alberta, Canada approached this integration challenge is described below. Target audience: This topic is pertinent to those working at a systems level in healthcare, government and the third sector. Who was engaged: In developing this approach government, health system planners, and a variety of third sector representatives, typically “umbrella” organizations representing a number of individual groups, were involved. What was done: With a single healthcare system divided into five administrative zones, we used the approach of doing centrally, zonally and locally that which made sense to do at those levels. Third sector actors functioning at those levels were engaged with their health system counterparts. Joint committees, accountable only to the members, were typically established to set a common vision and to coordinate activities in support of that joint vision. Wherever possible, an asset-based community development approach was used to identify what services existed at the various levels, service deficits, the wants and needs of individuals and communities, and the way in which the community could be supported to address those needs and wishes. From an infrastructure perspective, the health system, government and third sector leadership established mechanisms to facilitate cooperation. Results: Creating formal linkages between the health system and third sector, at all levels, was extremely helpful for the healthcare system to understand community needs and factors impacting health. The third sector found the relationship helpful to focus their efforts on programs or interventions which most effectively impacted health and wellness. Individuals and communities benefitted from an integrated approach to health and wellness. Learnings: Giving up control, on the part of the health system, was initially uncomfortable. However, the effectiveness of joint committees accountable to the members, rather than to a hierarchy, was found to be an extremely effective way of working together. At a more local level, allowing communities to determine priorities and approaches similarly resulted in much more effective and productive relationships in meeting the needs of the community, the healthcare system and its providers. Components of the quadruple/quintuple aim were much more effectively addressed than by using a medical model of community engagement. Next steps: From a health system perspective, we plan to use this approach at a community level. However, we find that our workforce will need to be adapted to include those who have skills in developing and maintaining relationships, are comfortable working in complex systems and with uncertainty, and an ability to adapt in keeping with a learning health system.
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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 | 0.040 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.002 | 0.042 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".