Unscheduled general surgery has higher costs for older adults
Bibliographic record
Abstract
BACKGROUND: With health care costs increasing, the cost of caring for older adults is rising. Understanding the costs of surgical care for older adults is crucial in planning for health care services. We hypothesize that increasing age predicts increasing surgical inpatient costs. METHODS: We conducted a retrospective analysis of general surgical inpatient costs at 4 hospitals over 2 fiscal years. We assessed the cost and number of procedures by age, procedure, hospital, cost category and surgical urgency. Costs were compared between surgical risk profile, urgency and age. Cost differences of 10% or more were considered clinically important. RESULTS: We examined the surgical inpatient costs for 12 070 procedures, representing 84% of all admissions in the region. The average cost was $4351 for scheduled admissions and $4054 for unscheduled admissions. Only unscheduled admissions resulted in higher costs in older age groups, more than doubling in patients aged 80 years and older undergoing low- and moderate-risk unscheduled surgery. The higher costs for older adults was primarily because of higher postoperative costs. In addition, the screening of candidates for elective surgery may have resulted in preoperative medical optimization leading to decreased admission costs. CONCLUSION: Older adults requiring surgery incur increased costs only if admitted for emergency surgery. The cost increase associated with unscheduled admissions was primarily for increased postoperative costs. Innovative programs to reduce costs for postoperative care for older adults undergoing emergency surgery should be investigated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".