Short and Mid-Term Economic Impact of Pulmonary Artery Catheter Use in Adult Cardiac Surgery: A Hospital and Integrated Health System Perspective
Bibliographic record
Abstract
OBJECTIVE: A monitoring pulmonary artery catheter (PAC) is utilized in approximately 34% of the US cardiac surgical procedures. Increased use of PAC has been reported to have an association with complication rates: significant decreases in new-onset heart failure (HF) and respiratory failure (RF), but increases in bacteremia and urinary tract infections. We assessed the impact of increasing PAC adoption on hospital costs among cardiac surgery patients for US-based healthcare systems. METHODS: An Excel-based economic model calculated annualized savings for a US hospital with various cardiac surgical volumes and PAC adoption rates. A second model, for an integrated payer-provider health system, analyzed outcomes/costs resulting from the cardiac surgical admission and for the treatment of persistent HF and RF complications in the year following surgery. Model inputs were extracted from published literature, and one-way and probabilistic sensitivity analyses were performed. RESULTS: For an acute care hospital with 500 procedures/year and 34% PAC adoption, annualized savings equalled $61,806 vs no PAC utilization. An increase in PAC adoption rate led to increased savings of $134,751 for 75% and $170,685 for 95% adoption. Savings ranged from $12,361 to $185,418 at volumes of 100 and 1500 procedures/year, respectively. For an integrated payer-provider health system with the base-case scenario of 3845 procedures/year and 34% PAC adoption, estimated savings were $596,637 for the combined surgical index admission and treatment for related complications over the following year. CONCLUSION: PAC utilization in adult cardiac surgery patients results in reduced costs for both acute care hospitals and payer-provider integrated health systems.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".