Chronic Care Model Strategies In The United States And Germany Deliver Patient-Centered, High-Quality Diabetes Care
Bibliographic record
Abstract
Improving the quality of care for chronic diseases is an important issue for most health care systems in industrialized nations. One widely adopted approach is the Chronic Care Model (CCM), which was first developed in the late 1990s. In this article we present the results from two large surveys in the United States and Germany that report patients' experiences in different models of patient-centered diabetes care, compared to the experiences of patients who received routine diabetes care in the same systems. The study populations were enrolled in either Geisinger Health System in Pennsylvania or Barmer, a German sickness fund that provides medical insurance nationwide. Our findings suggest that patients with type 2 diabetes who were enrolled in the care models that exhibited key features of the CCM were more likely to receive care that was patient-centered, high quality, and collaborative, compared to patients who received routine care. This study demonstrates that quality improvement can be realized through the application of the Chronic Care Model, regardless of the setting or distinct characteristics of the program.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".