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Record W2027009401 · doi:10.1377/hlthaff.2014.0428

Chronic Care Model Strategies In The United States And Germany Deliver Patient-Centered, High-Quality Diabetes Care

2014· article· en· W2027009401 on OpenAlexaff
Stephanie Stock, James Pitcavage, Dušan Simić, Sibel Altin, Christian Gräf, Wen Feng, Thomas Graf

Bibliographic record

VenueHealth Affairs · 2014
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsInstitute of Health Economics
Fundersnot available
KeywordsChronic careMedicineDiabetes mellitusQuality (philosophy)GerontologyMEDLINEHealth careFamily medicineNursingChronic diseasePolitical science

Abstract

fetched live from OpenAlex

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.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.019
GPT teacher head0.299
Teacher spread0.279 · 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 designQualitative
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

Citations44
Published2014
Admission routes1
Has abstractyes

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