National trends in hospital-acquired preventable adverse events after major cancer surgery in the USA
Bibliographic record
Abstract
OBJECTIVES: While multiple studies have demonstrated variations in the quality of cancer care in the USA, payers are increasingly assessing structure-level and process-level measures to promote quality improvement. Hospital-acquired adverse events are one such measure and we examine their national trends after major cancer surgery. DESIGN: Retrospective, cross-sectional analysis of a weighted-national estimate from the Nationwide Inpatient Sample (NIS) undergoing major oncological procedures (colectomy, cystectomy, oesophagectomy, gastrectomy, hysterectomy, lung resection, pancreatectomy and prostatectomy). The Agency for Healthcare Research and Quality Patient Safety Indicators (PSIs) were utilised to identify trends in hospital-acquired adverse events. SETTING: Secondary and tertiary care, US hospitals in NIS PARTICIPANTS: A weighted-national estimate of 2 508 917 patients (>18 years, 1999-2009) from NIS. PRIMARY OUTCOME MEASURES: Hospital-acquired adverse events. RESULTS: 324 852 patients experienced ≥1-PSI event (12.9%). Patients with ≥1-PSI experienced higher rates of in-hospital mortality (OR 19.38, 95% CI 18.44 to 20.37), prolonged length of stay (OR 4.43, 95% CI 4.31 to 4.54) and excessive hospital-charges (OR 5.21, 95% CI 5.10 to 5.32). Patients treated at lower volume hospitals experienced both higher PSI events and failure-to-rescue rates. While a steady increase in the frequency of PSI events after major cancer surgery has occurred over the last 10 years (estimated annual % change (EAPC): 3.5%, p<0.001), a concomitant decrease in failure-to-rescue rates (EAPC -3.01%) and overall mortality (EAPC -2.30%) was noted (all p<0.001). CONCLUSIONS: Over the past decade, there has been a substantial increase in the national frequency of potentially avoidable adverse events after major cancer surgery, with a detrimental effect on numerous outcome-level measures. However, there was a concomitant reduction in failure-to-rescue rates and overall mortality rates. Policy changes to improve the increasing burden of specific adverse events, such as postoperative sepsis, pressure ulcers and respiratory failure, are required.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".