Health Care Use and Costs in the Decade After Identification of Type 1 and Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To analyze trends in health care costs in the decade after identification of diabetes, contrasting type 1 and 2 diabetes. RESEARCH DESIGN AND METHODS: The Canadian National Diabetes Surveillance System criteria were applied to administrative databases to identify incident diabetes cases in 1992. Cases were categorized as type 1 or type 2 diabetes based on patterns of drug use. Per capita health care costs (in 2001 Canadian dollars) for five resource categories were estimated according to the type of diabetes, for the year before identification (1991) and 10 years after (1992-2001) identification of the cases. RESULTS: We identified 156 type 1 and 3,469 type 2 incident cases of diabetes, from a population base of approximately 950,000. The mean (+/-SD) age of case subjects at index was 61.2 +/- 16.7 years, and 54% of subjects were male. Overall annual per capita health expenditures rose considerably in the year after identification of diabetes but then stabilized at a lower level for the next 9 years, ranging from $3,800 to $4,400. From 1992 to 2001, diabetic individuals used $137.1 million in health care resources, most of which (96%) was attributable to type 2 diabetes. The average 10-year cost per individual with diabetes was $37,820 ($33,684 per type 1 and $38,006 per type 2 diabetes case; adjusted P = 0.45). CONCLUSIONS: Total health expenditures for diabetes are driven by the much larger prevalence of type 2 compared with type 1 diabetes. Policymakers need to acknowledge and allocate resources for diabetes prevention and management accordingly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".