Continuity of care in the ambulatory sector and hospital admissions among patients with heart failure in Germany
Bibliographic record
Abstract
BACKGROUND: Heart failure is one of the most cost-intensive chronic diseases and the most common cause of hospitalization. More than 60% of the treatment costs of heart failure are incurred in the inpatient sector in Germany. However, hospital admissions due to heart failure are considered to be potentially avoidable through effective and continuous ambulatory care. Our aim is to examine whether continuity in ambulatory care is associated with hospitalizations due to heart failure. METHODS: Using insurance claims data from Germany's biggest statutory health insurance company, we defined three measures of continuity of care: Continuity of Care Index (COCI), Usual Provider Index (UPC) and the Sequential Continuity Index (SECON). We analyzed whether these measures are associated with hospitalization due to heart failure using separate logistic regression models. We controlled for a wide range of covariates such as sex, age and the Charlson comorbidity index. RESULTS: Data of 382 118 heart failure patients were included in the analyses. Index values range from 0.77 to 0.89. Results of logistic regression analyses indicate that the continuity indices COCI, UPC and SECON based on visits to general practitioners (GPs), cardiologists and internists are negatively associated with the probability of hospitalization whereas of the continuity indices based on GP visits only SECON is significantly associated with hospitalization. CONCLUSION: The results indicate that the overall continuity in the ambulatory sector is high for heart failure patients in Germany. Public policy should, nevertheless, focus on increasing sequential continuity of specialist and generalist ambulatory care as this was found to be significantly associated with a reduced likelihood of hospitalization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".