Toward a Consensus on Centralization in Surgery
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
OBJECTIVES: To critically assess centralization policies for highly specialized surgeries in Europe and North America and propose recommendations. BACKGROUND/METHODS: Most countries are increasingly forced to maintain quality medicine at a reasonable cost. An all-inclusive perspective, including health care providers, payers, society as a whole and patients, has ubiquitously failed, arguably for different reasons in environments. This special article follows 3 aims: first, analyze health care policies for centralization in different countries, second, analyze how centralization strategies affect patient outcome and other aspects such as medical education and cost, and third, propose recommendations for centralization, which could apply across continents. RESULTS: Conflicting interests have led many countries to compromise for a health care system based on factors beyond best patient-oriented care. Centralization has been a common strategy, but modalities vary greatly among countries with no consensus on the minimal requirement for the number of procedures per center or per surgeon. Most national policies are either partially or not implemented. Data overwhelmingly indicate that concentration of complex care or procedures in specialized centers have positive impacts on quality of care and cost. Countries requiring lower threshold numbers for centralization, however, may cause inappropriate expansion of indications, as hospitals struggle to fulfill the criteria. Centralization requires adjustments in training and credentialing of general and specialized surgeons, and patient education. CONCLUSION/RECOMMENDATIONS: There is an obvious need in most areas for effective centralization. Unrestrained, purely "market driven" approaches are deleterious to patients and society. Centralization should not be based solely on minimal number of procedures, but rather on the multidisciplinary treatment of complex diseases including well-trained specialists available around the clock. Audited prospective database with monitoring of quality of care and cost are mandatory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 it