Policy Versus Practice: Facilitators and Barriers of Chronic Care Integration in Dutch General Practice – a Survey Study
Bibliographic record
Abstract
Introduction: Multimorbidity challenges quality and sustainability of healthcare systems. Care groups were introduced in the Netherlands to promote integration of chronic primary care, but it remains unknown to which degree they facilitate this. This study therefore aims to determine whether Dutch general practices perceive themselves to be capable of delivering integrated chronic care and uncover the role of care groups. Methods: We performed a survey study amongst 39 care groups and 65 healthcare providers within general practices (GPs and nurse practitioners). Results: 43% of healthcare providers within general practices are (very) dissatisfied with capabilities for chronic care to patients and 56% do not feel capable of delivering integrated care. Care groups and providers show alignment in their perception of some of the most important facilitators and barriers such as motivation and lack of time, but other factors are valued differently at both levels. Discussion: Our findings show inability of general practices to deliver integrated chronic care despite a health system that is inherently supportive of care integration and point to a mismatch between barriers and facilitators amongst practices and care groups, resulting in providers partly relying on their motivation in accommodating integrated chronic care. Conclusion: General practices are not sufficiently supported by care groups and national policies in delivering integrated chronic care. The identified mismatch between policy and practice warrants redesign of support from care groups to align policies with identified barriers and facilitators at the provider level.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".