Improving performance in diabetes care: a multicomponent intervention.
Bibliographic record
Abstract
CONTEXT: Compliance with recommendations from the American Diabetes Association for management of patients with diabetes is not optimal. Changing physician practice patterns with provider-focused interventions can be difficult. We report results after implementation of a type 2 diabetes mellitus guideline. OBJECTIVE: To increase the annual rate of microalbumin/urine protein testing, dilated eye examinations, and foot examinations for patients with diabetes and to reduce overall levels of hemoglobin A1c (Hb A1c). DESIGN: Before-after study. INTERVENTION: From April 1996 to June 1998, a guideline on type 2 diabetes mellitus was implemented with multicomponent interventions. These included small group educational sessions led by opinion leaders, an electronic version of the guideline, audit with feedback, and enhanced clinical orders support. Medical records of random samples of patients with diabetes were audited for specific diabetes performance measures on a monthly basis. Baseline data were compared with results at the end of the implementation effort. SETTING: Southeastern Minnesota, excluding Olmsted County. PARTICIPANTS: Adult patients seen at one practice of 18 general internists. OUTCOME MEASURES: Outcome measures included Hb A1c values and annual performance of a urine protein test, foot examination, and dilated eye examination. RESULTS: Gradual, sustained; and statistically significant improvements in the three annual performance measures were observed. Urine protein testing increased from 24% to 66% (P = 0.001), dilated eye examinations increased from 63% to 84% (P = 0.001), and foot examinations increased from 86% to 97% (P = 0.001). Mean Hb A1c values +/- SD also improved from 7.8% +/- 1.0% to 7.1% +/- 0.7% (P < 0.001) in patients who received continuing care for diabetes. CONCLUSIONS: Statistically significant improvements were observed after continuous improvement efforts were focused on providers in an individual group practice. When used to implement a diabetes guideline, such interventions may improve delivery of services and reduce Hb A1c levels in patients with diabetes.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".