Quality measure attainment in patients with type 2 diabetes mellitus.
Bibliographic record
Abstract
OBJECTIVES: This study examined the demographics, comorbidities, clinical characteristics, and treatments of people with type 2 diabetes mellitus (T2DM) treated with metformin and sulfonylurea as well as an elderly subgroup. Achievement of predefined quality measure goals (glycated hemoglobin [A1C], blood pressure [BP], low-density lipoprotein cholesterol [LDL-C], body mass index [BMI]) and their association with diabetes-related healthcare costs were assessed. STUDY DESIGN: The study applied a retrospective longitudinal cohort design. METHODS: Health insurance claims and electronic medical records from 14,532 adults with T2DM (2007- 2011) were used to identify a sample receiving metformin and sulfonylurea (MET+SU) concomitantly. The index date was the first dispensing of MET+SU after 6 months of eligibility. Clinical characteristics were assessed during baseline. Quality measure attainment (A1C <8%, BP <140/90 mm Hg, LDL-C level <100 mg/dL, BMI <30 kg/m²), was evaluated during the 12 months following the index date. Association between attainment and diabetes-related costs was evaluated using non-parametric bootstrap methods adjusting for imbalance in baseline characteristics between cohorts. RESULTS: Among 2044 patients, including 1283 patients 65 years and older, hyperlipidemia, hypertension, and cardiovascular disease were the most common baseline comorbidities. Quality measure goal attainment was 63.9% for A1C, 33.1% for BP, 68.2% for LDL-C level, and 34.4% for BMI, and was associated with significantly lower diabetes-related costs per patient per year compared with nonattainment (adjusted mean cost differences: -$1445 for A1C; -$1218 for BMI; -$2029 for A1C and BMI; -$2073 for A1C, BMI, and BP; all P <.05). CONCLUSION: This study highlights the high incidence of comorbidities and potential financial implications of attaining T2DM quality outcomes.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".