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Risk stratification models fail to predict hospital costs of cardiac surgery patients
1Department of Cardiothoracic Surgery, University of Cologne, Kerpener Str. 62, 50924 Cologne, Germany. khosro.hekmat@uk-koeln.de
Insights
Common risk scores do not predict cardiac surgery costs. Length of ICU stay is a strong predictor of total hospital costs for these patients.
Area of Science:
- Cardiovascular Surgery
- Health Economics
- Medical Informatics
Background:
- Assessing financial implications in cardiac surgery is crucial for resource allocation.
- Existing risk stratification models are widely used but their ability to predict costs is uncertain.
Purpose of the Study:
- To evaluate the predictive accuracy of seven common risk stratification models for total hospital costs in cardiac surgical patients.
- To identify reliable predictors of hospital costs in this patient population.
Main Methods:
- Prospective study of 252 adult cardiac surgery patients undergoing cardiopulmonary bypass (CPB).
- Patients were assessed using seven risk stratification systems (EuroSCORE, Cleveland, Parsonnet, Ontario, French, Pons, CABDEAL).
- Total hospital costs, including preoperative, intraoperative, and fixed costs, were calculated; correlation with risk scores and ICU length of stay (LOS) was analyzed using linear regression and Spearman correlation.
Main Results:
- Risk stratification models showed weak correlation with total hospital costs (Spearman r < 0.32).
- Length of ICU stay demonstrated a strong correlation with total hospital costs (Spearman r = 0.94).
- The study included diverse cardiac surgical procedures, with CABG being the most frequent (n=175).
Conclusions:
- Length of ICU stay is a significant and reliable predictor of total hospital costs in cardiac surgery.
- Current common risk stratification models are inadequate for accurately predicting total hospital costs in cardiac surgical patients.
- Further research may be needed to develop cost-predictive models for cardiac surgery.
Background:
The aim of this prospective study was to determine if commonly used risk stratification models can predict total hospital costs in cardiac surgical patients.
Methods:
Between October 1st and December 31st 2003, all consecutive adult patients undergoing cardiac surgery on CPB at our institution were classified using seven risk stratification scoring systems: EuroSCORE, Cleveland, Parsonnet, Ontario, French, Pons, and CABDEAL. Total hospital costs for each patient were calculated on a daily basis including preoperative diagnostic tests, operating room costs, disposable materials, drugs, blood components, costs for personnel, and hospital fixed-costs. Linear regression analysis was used to determine the correlation between costs and the seven risk stratifications models as well as length of stay (LOS) on ICU. The Spearman correlation coefficient was calculated from the regression line, and an analysis of residuals was performed to determine the quality of the regression.
Results:
A total of 252 patients were operated for CABG (n=175), valve (n=39), CABG plus valve (n=21), thoracic aorta (n=13) and miscellaneous (2 myxoma, 1 ASD, 1 pulmonary embolism). Mean age of the patients was 66.0+/-11.4 years, 29.4% were female. LOS on ICU was 3.3+/-6.3 days and the 30-day mortality rate was 6.7%. Spearman correlation between the seven risk stratification models and hospital costs was below r=0.32 (p=0.0001), but was r=0.94 (p=0.0001) between ICU LOS and costs.
Conclusions:
Total hospital costs can be identified by length of ICU stay. None of the common risk stratification models accurately predicted total hospital costs in cardiac surgical patients.
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