Economic Consequences of Epidemiological Changes in Diabetes in Middle-Income Countries
Bibliographic record
Abstract
OBJECTIVE: To identify the costs and economic consequences of expected changes in the demand for health care services for type 2 diabetes in the three main public institutions of the Mexican health care system. RESEARCH DESIGN AND METHODS: The cost evaluation method to estimate direct and indirect costs was based on instrumentation and consensus techniques. To estimate the costs and epidemiological changes for 2003-2005, three probabilistic models were constructed according to the Box-Jenkins technique. RESULTS: Comparing the economic impact in 2003 versus 2005 (P < 0.05), there is a 26% increase in financial requirements. The total amount for diabetes in 2005 (in U.S. dollars) will be 317,631,206, dollars including 140,410,816 dollars in direct costs and 177,220,390 dollars in indirect costs. The total direct costs, representing financial requirements to provide health care for expected cases of type 2 diabetes and its main complications in the three main public institutions in Mexico, up to 2005, will be 37,079,587 dollars for the Ministry of Health (or Secretaría de Salud [SSA], serving the uninsured population) and 103,331,235 dollars for the Mexican Social Security Institute, or Instituto Mexicano del Seguro Social (IMSS), and the Institute for Social Security and Services for State Workers, or Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado (ISSSTE), both of which serve the insured population. CONCLUSIONS: Our data suggest that changes in the demand for health care services for patients with diabetes will continue with an increasing trend, mainly in the insured population. In economic terms, the results of direct and indirect costs are one of the main challenges to be solved to decrease the economic burden that diabetes represents for the population, the health care institutions, and for society as a whole.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".