An Information Sharing Framework: Supporting Collaborative and Integrated Service Delivery
Bibliographic record
Abstract
Background:The Information Sharing Framework enhances the degree of collaboration and integration among client-serving organizations providing mental health supports across all relevant sectors by providing guidance in navigating the complexities of privacy legislation; managing information appropriately; considerations in adapting policies and practices; and tools to use in collaborative service delivery. Approach:The identified issue was that information was not being shared as readily or effectively as it should be when organizations need to collaborate, thereby limiting and at times impeding the effectiveness of collaboration. In order to better understand the issue, a broad swath of organizations was invited to participate in the development of an enhanced service delivery approach, which ended up being the Framework. Input and participation were obtained from a wide variety of people serving organizations including non-profit agencies, associations (e.g. United Way), health organizations (e.g. PCNs), registrars from health profession colleges, school boards, police services, as well as provincial government, and privacy commissioner's staff, among others. Participants provided input as the Framework was developed, with inputs and comments assisting in shaping it as it evolved. The Framework is meant to address two main areas: the first being the fact that organizations in different sectors are subject to differing privacy legislation, which, by and large is neither harmonized, nor consistently interpreted, and in many jurisdictions not applicable to the non-profit sector. The second area has more to do with identifying areas for consideration that may be seen as more structural in nature, including governance, roles and responsibilities, policies and practices, and information management. The Framework provides support to organizations who wish or need to collaborate effectively when providing services to individuals and families. While it was developed in support of those delivering mental health supports and services, it can easily apply to any people-facing services in the health and social service sectors. Results:The outcome of the work is the development of the Information Sharing Framework, which provides fairly comprehensive guidance on what organizations wishing to develop or enhance their collaborative service delivery need to consider and implement. It also includes a number of resources and tools, that can support both individual agencies that are seeking to improve their information management policies and practices, as well as partnerships or groups of organizations that need to determine how they will work together more effectively, and how they will address onboarding of members.The Framework is being rolled out for use in Alberta, where it is in use by a number of groups and organizations, and is being offered for adaptation and adoption in other jurisdictions. Implications:The Framework addresses a number of areas that many jurisdictions are struggling with, and can be readily adapted for their use. The themes that are spoken to are broadly applicable, and focus on ensuring that organizations do not lose sight that privacy legislation was not meant to impede access by individuals and families to effective and necessary services delivered by organizations working collaboratively, creating the 'basket of supports' that are often alluded to. It sets out how to create that basket.Converge Mental Health Coalition has made the Framework materials available for use by hosting them on their website. In recognition that there will be a need to adapt it for use by jurisdictions other than Alberta, we are reaching out to various organizations in other jurisdictions to determine if there is interest in adapting and adopting the Framework for use by those jurisdictions. We are having a number of conversations with various organizations to that end.The package is available at Information Sharing Framework (Our Work - Converge (convergementalhealth.org)
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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 | 0.088 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.017 | 0.029 |
| Open science | 0.008 | 0.026 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".