A province wide review of transition practices for young adult patients with type 1 diabetes
Bibliographic record
Abstract
RATIONALE, AIMS, AND OBJECTIVES: Many studies on the transition from paediatric to adult care focus on practices within a single institution or program. We examine the transition for young adults with type 1 diabetes across an entire Canadian province with a small, mostly rural population and high rates of type 1 diabetes: Newfoundland and Labrador (NL). Our aim is to determine how transition is occurring across the jurisdiction and identify methods for improving clinical services for paediatric patients with a chronic condition during their move into adult care. METHODS: A provincial diabetes database and hospital admission data were reviewed for a cohort of young adults with type 1 diabetes who transitioned into adult care. Semi-structured interviews were conducted with paediatric and adult diabetes providers. RESULTS: Between 2008 and 2013, 93 patients with type 1 diabetes transitioned into adult care. Rates of diabetes-related hospitalizations increased from 15.6/100 person-years in the 3 years before their 18th birthday to 16.7/100 person-years in the three-year period after. Between 2017 and 2019, 15 interviews were conducted across the province's four regional health authorities. Various models of transition care are being employed, reflecting staff and resource availability in different centres. While no formal transition program was identified in either region, some providers, particularly in rural areas, reported being comfortable with their current transition practices. Suggested improvements included more structured processes, shared educational resources, expanding the role played by primary care physicians, and a dedicated transfer clinic. CONCLUSIONS: We found different approaches for transitioning patients with diabetes into adult care across NL. Yet this variation may not negatively impact patient outcomes, particularly in rural areas. The approach we employed of combining reviews of administration data with a detailed analysis of current processes could be employed in other jurisdictions to identify appropriate quality improvement initiatives.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".