New 2011 Survey Of Patients With Complex Care Needs In Eleven Countries Finds That Care Is Often Poorly Coordinated
Bibliographic record
Abstract
Around the world, adults with serious illnesses or chronic conditions account for a disproportionate share of national health care spending. We surveyed patients with complex care needs in eleven countries (Australia, Canada, France, Germany, the Netherlands, New Zealand, Norway, Sweden, Switzerland, the United Kingdom, and the United States) and found that in all of them, care is often poorly coordinated. However, adults seen at primary practices with attributes of a patient-centered medical home--where clinicians are accessible, know patients' medical history, and help coordinate care--gave higher ratings to the care they received and were less likely to experience coordination gaps or report medical errors. Throughout the survey, patients in Switzerland and the United Kingdom reported significantly more positive experiences than did patients in the other countries surveyed. Reported improvements in the United Kingdom tracked with recent reforms there in health care delivery. Patients in the United States reported difficulty paying medical bills and forgoing care because of costs. Our study indicates a need for improvement in all countries through redesigning primary care, developing care teams accountable across sites of care, and managing transitions and medications well. The United States in particular has opportunities to learn from diverse payment innovations and care redesign efforts under way in the other study countries.
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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 | 0.001 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".