Designing an Integrated Care Initiative for Vulnerable Families: Operationalisation of Realist Causal and Programme Theory, Sydney Australia
Bibliographic record
Abstract
INTRODUCTION: In July 2015 Sydney Local Health District (SLHD) implemented an integrated care initiative for vulnerable families in the Inner West region of Sydney, Australia. The initiative was designed as a cross-agency care coordination network that would ensure that vulnerable families: had their complex health and social needs met; kept themselves and their children safe; and were connected to society. We will describe the development of the design that drew on earlier realist causal and program theoretical work. METHODS: Realist causal and program theory were used to inform the collaborative design of an initiative for vulnerable families. The collaborative design process included: identification of desirable and undesirable outcomes and contextual factors, stakeholder consultation, interagency planning, and development of a service proposal. RESULTS: The design elements included: identification of vulnerable family cohorts; care coordination; evidence-informed intervention(s); general practice engagement and support; family health improvement; placed-based neighbourhood initiatives; interagency system change and collaborative planning; monitoring of individual and family outcomes; and evaluation. CONCLUSIONS: The design study described advances toward the implementation of a whole-of-government integrated health and social care initiative. The initiative was designed as a cross-agency care coordination network that would ensure that vulnerable families: had their complex health and social needs met; kept themselves and their children safe; and were connected to society. In so doing we aim to break intergenerational cycles of poverty, violence and crime, poor education and employment opportunities, psychopathology, and poor lifestyle and health behaviours, through strengthening family resilience, improving access to services, and addressing the social determinants of health and wellbeing.
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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 | 0.065 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".