The development of integrated diabetes care in the Netherlands: a multiplayer self-assessment analysis
Bibliographic record
Abstract
BACKGROUND: Since recent years Dutch diabetes care has increasingly focused on improving the quality of care by introducing the concept of care groups (in Dutch: 'zorggroepen'), care pathways and improving cooperation with involved care professionals and patients. This study examined how participating actors in care groups assess the development of their diabetes services and the differences and similarities between different stakeholder groups. METHODS: A self-evaluation study was performed within 36 diabetes care groups in the Netherlands. A web-based self-assessment instrument, based on the Development Model for Integrated Care (DMIC), was used to collect data among stakeholders of each care group. The DMIC defines nine clusters of integrated care and four phases of development. Statistical analysis was used to analyze the data. RESULTS: Respondents indicated that the diabetes care groups work together in well-organized multidisciplinary teams and there is clarity about one another's expertise, roles and tasks. The care groups can still develop on elements related to the management and monitoring of performance, quality of care and patient-centeredness. The results show differences (p < 0.01) between three stakeholders groups in how they assess their integrated care services; (1) core players, (2) managers/directors/coordinators and (3) players at a distance. Managers, directors and coordinators assessed more implemented integrated care activities than the other two stakeholder groups. This stakeholder group also placed their care groups in a further phase of development. Players at a distance assessed significantly less present elements and assessed their care group as less developed. CONCLUSIONS: The results show a significant difference between stakeholder groups in the assessment of diabetes care practices. This reflects that the professional disciplines and the roles of stakeholders influence the way they asses the development of their integrated care setting, or that certain stakeholder groups could be less involved or informed.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".