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Record W2140551504 · doi:10.1186/1472-6963-3-7

Cost of managing complications resulting from type 2 diabetes mellitus in Canada

2003· article· en· W2140551504 on OpenAlexaffabout
Judith A. O’Brien, Amanda R. Patrick, J. Jaime

Bibliographic record

VenueBMC Health Services Research · 2003
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsMcGill UniversityRoyal Victoria Hospital
Fundersnot available
KeywordsHealth administrationFormularyMedicineNursing researchHealth informaticsPublic healthHealth economicsIndirect costsUnit (ring theory)Cost driverCost databaseMedical emergencyIntensive care medicineOperations managementFamily medicineBusinessNursingDatabaseMarketing

Abstract

fetched live from OpenAlex

BACKGROUND: Decision makers need to have Canadian-specific cost information in order to develop an accurate picture of diabetes management. The objective of this study is to estimate direct medical costs of managing complications of diabetes. Complication costs were estimated by applying unit costs to typical resource use profiles. For each complication, the event costs refer to those associated with the acute episode and subsequent care in the first year. State costs are the annual costs of continued management. Data were obtained from many Canadian sources, including the Ontario Case Cost Project, physician and laboratory fee schedules, formularies, reports, and literature. All costs are expressed in 2000 Canadian dollars. RESULTS: Major events (e.g., acute myocardial infarction: 18,635 dollars event cost; 1,193 dollars state cost), generate a greater financial burden than early stage complications (e.g., microalbuminuria: 62 dollars event cost; 10 dollars state cost). Yet, complications that are initially relatively low in cost (e.g., microalbuminuria) can progress to more costly advanced stages (e.g., end-stage renal disease, 63,045 dollars state cost). CONCLUSIONS: Macrovascular and microvascular complication costs should be included in any economic analysis of diabetes. This paper provides Canadian-based cost information needed to inform critical decisions about spending limited health care dollars on emerging new therapies and public health initiatives.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.071
GPT teacher head0.377
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations119
Published2003
Admission routes2
Has abstractyes

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