Integrating care for individuals with FASD: results from a multi-stakeholder symposium
Bibliographic record
Abstract
BACKGROUND: Fetal Alcohol Spectrum Disorder (FASD) has a significant impact on communities and systems such as health, education, justice and social services. FASD is a complex neurodevelopmental disorder that results in permanent disabilities and associated service needs that change across affected individuals' lifespans. There is a degree of interdependency among medical and non-medical providers across these systems that do not frequently meet or plan a coordinated continuum of care. Improving overall care integration will increase provider-specific and system capacity, satisfaction, quality of life and outcomes. METHODS: We conducted a consensus generating symposium comprised of 60 experts from different stakeholder groups: Allied & Mental Health, Education, First Nations & Métis Health, Advocates, Primary Care, Government Health Policy, Regional FASD Coordinators, Social Services, and Youth Justice. Research questions addressed barriers and solutions to integration across systems and group-specific and system-wide research priorities. Solutions and consensus on prioritized lists were generated by combining the Electronic Meeting System approach with a modified 'Nominal Group Technique'. RESULTS: FASD capacity (e.g., training, education, awareness) needs to be increased in both medical and non-medical providers. Outcomes and integration will be improved by implementing: multidisciplinary primary care group practice models, FASD system navigators/advocates, and patient centred medical homes. Electronic medical records that are accessible to multiple medical and non-medical providers are a key tool to enhancing integration and quality. Eligibility criteria for services are a main barrier to integration across systems. There is a need for culturally and community-specific approaches for First Nations communities. CONCLUSIONS: There is a need to better integrate care for individuals and families living with FASD. Primary Care is well positioned to play a central and important role in facilitating and supporting increased integration. Research is needed to better address best practices (e.g., interventions, supports and programs) and long-term individual and family outcomes following a diagnosis of FASD.
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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 | 0.051 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".