Managing the performance of general practitioners and specialists referral networks: A system for evaluating the heart failure pathway
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High quality chronic disease management requires coordinated care across different healthcare settings, involving multidisciplinary teams of professionals, and performance evaluation systems able to measure this care. Inter-organizational performance should be measured considering the professional relationships between general practitioners (GPs) and specialists, who are usually linked through informal referral networks. The aim of this paper is to identify and evaluate the performance of naturally occurring networks of GPs and hospital-based specialists providing care for congestive heart failure (CHF) patients in Tuscany, Italy. The analysis focuses on the identification and classification of networks, following CHF patients (n = 15,841) through primary care and inpatient care using administrative data, and on the assessment of process and outcome indicators for CHF patients in these referral networks. We demonstrate the existence of informal links between GPs and hospitals based on patterns of patient flow. These networks which are not geographically based vary in the intensity of relationships and quality of care. Such referral networks may represent the most effective accountability level for chronic disease management, since they encompass the multiple care settings experienced by patients. Overall, an integrated approach to evaluation and performance management that considers the naturally occurring links between professionals working in different settings may enable more efficient, integrated care and quality improvements.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it