A Value-driven Outcomes Analysis of Cost Savings Due to Complication Prevention

Sean M. Stokes, Courtney L. Scaife, Benjamin S. Brooke,Robert E. Glasgow, Sean J. Mulvihill,Samuel R. G. Finlayson,Thomas K. Varghese

semanticscholar(2021)

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摘要
Objective: Surgical complications have substantial impact on healthcare costs. We propose an analysis of the financial impact of postoperative complications. Summary of Background Data: Both complications and preoperative patient risk have been shown to increase costs following surgery. The extent of cost increase due to specific complications has not been well described. Methods: A single institution’s American College of Surgeons National Surgical Quality Improvement Program data was queried from 2012 to 2018 and merged with institutional cost data for each encounter. A mixed effects multivariable generalized linear model was used to estimate the mean relative increase in hospital cost due to each complication, adjusting for patient and procedure-level fixed effects clustered by procedure. Potential savings were calculated based on projected decreases in complication rates and theoretical hospital volume. Results: There were 11,897 patients linked between the 2 databases. The rate of any American College of Surgeons National Surgical Quality Improvement Program complication was 11.7%. The occurrence of any complication resulted in a 1.5-fold mean increase in direct hospital cost [95% confidence interval (CI) 1.49–1.58]. The top 6 most costly complications were postoperative septic shock (4.0-fold, 95% CI 3.58–4.43) renal insufficiency/failure (3.3-fold, 95% CI 2.91–3.65), any respiratory complication (3.1-fold, 95% CI 2.94–3.36), cardiac arrest (3.0-fold, 95% CI 2.64–3.46), myocardial infarction (2.9-fold, 95% CI 2.43–3.42) and mortality within 30 days (2.2-fold, 95% CI 2.01–2.48). Length of stay (6.5 versus 3.2 days, P < 0.01), readmission rate (29.1% vs 3.1%, P < 0.01), and discharge destination outside of home (20.5% vs 2.7%, P < 0.01) were significantly higher in the population who experienced complications. Conclusions: Decreasing complication rates through preoperative optimization will improve patient outcomes and lead to substantial cost savings.
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