Exploring resource implications and models of care for assessment and diagnosis of fetal alcohol spectrum disorder: A scoping review
Bibliographic record
Abstract
Previous reviews have examined annual mean costs of care for individuals with fetal alcohol spectrum disorder (FASD), costs of the health burden, costs to the justice system, productivity losses for caregivers, and both the monetary and nonmonetary costs of reduced quality of life. However, because there have been no published reviews focused on understanding the resource implications and specific service features for the assessment and diagnostic process for FASD, the current scoping review investigated the available evidence on these topics. Eligible studies were identified through a systematic search of six databases and included if they contained information on the potential costs or models of care associated with undertaking an assessment for FASD. Data were charted, underwent content analysis, and were reported according to the PRISMA extension for scoping reviews. Eleven studies were included in the final qualitative synthesis. The primary patient costs were attributed to the lengthy time required for diagnosis (up to 47 h). The primary service costs were attributed to costs of clinicians and support personnel and the involvement of multidisciplinary teams in the assessment process. Estimates of the specific dollar values of diagnostic costs were limited and varied between studies. Several models of care were explored, primarily in Canadian clinics, which aimed to capitalize on available services to improve accessibility and patient care and reduce service costs. This study provides important preliminary insights into the resource implications and models of care involved in the diagnostic assessment of FASD. However, the low number of available studies and variability in available data highlight the need for formal costing studies and detailed information gathering on available models of care to inform future clinical practice and policy development.
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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 | 0.039 | 0.165 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.024 | 0.022 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".