The impact of surgical experience on total hospital charges for minimally invasive prostatectomy: a population‐based study
Bibliographic record
Abstract
Study Type – Therapy (case series) Level of Evidence 4 What’s known on the subject? and What does the study add? Minimally invasive radical prostatectomy (MIRP) for the treatment of localized prostate cancer has rapidly gained increasing popularity over time. The current report highlights the importance of high surgical experience in regards to lowering MIRP hospital charges. OBJECTIVE • To evaluate the relationship between surgical volume (SV) and total hospital charges in patients undergoing minimally invasive radical prostatectomy (MIRP) for treatment of localized prostate cancer. PATIENTS AND METHODS • Within the Florida Hospital Inpatient Datafile, 2666 men who were treated with MIRP for prostate cancer between 2002–2008 were identified. • The SV was defined in two ways: annual caseload (AC) and each surgeons experience (SE) defined as the total number of procedures performed since entering the study until the time of each MIRP. RESULTS • The mean and median charges were respectively 38 852 and 31 511 US Dollars. AC ranged from 1–171 and SE varied from 1–500. Overall, 75.7 to 94% of surgeons were in the lowest AC tertile and 27 to 66% of patients were operated by low AC tertile surgeons. • After stratification according to AC tertiles, median charges were 41 564; 33 395 and 26 608 US Dollar for respectively low intermediate and high AC tertile categories. • Multivariable logistic regression models with generalized estimating equations revealed that the probability of charges above the median was reduced by respectively 38 and 68% in patients operated by intermediate SE (17–76 MIRPs) or high SE tertile (≥77 MIRPs) surgeons vs. low SE tertile (≤16 MIRPs) surgeons. CONCLUSIONS • High surgical experience reduces MIRP total hospital charges. • Despite this observation, even in 2008, 82% of MIRP surgeons were in the lowest AC tertile and contributed to 32% of all MIRPs.
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.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".