Predictors of hospital costs in patients submitted to heart surgery: the intensivist point of view

Background

Heart surgery (HS) has been considered one of the most cost consuming procedures in health care, therefore many strategies has been studied in order to reduce its final costs.

Objective

To evaluate factors collected during preoperative, per-operative and postoperative period in Surgical Intensive Care Unit (SICU) that could be correlated to higher hospital costs (HHC) of patients submitted to HS.

Methods

We retrospectively analyzed prospective collected data from a Customized Database System. Hospital cost data was available in 246 of 350 patients submitted to HS from June 2000 to November 2001. Applying linear regression and goodness-of-fit statistics to 62 variables obtained preoperative, peroperative and postoperative period in SICU we observed its correlation with HHC.

Results

Variables considered significant under multivariate analysis (R = 0.950, R² = 0.903, R² adjusted = 0.898) revealed higher hospital costs in the presence of pulmonary hypertension (PH) (P = 0.04), increased left atrial diameters (ILAD) (P = 0.013), use of anti-platelet agents in the previous 7 days (UAPA) (P = 0.006), intra-aortic balloon (IAB) use for extra-corporeal circulation delivery, admission SICU bicarbonate level (BL) (P = 0.0001), SICU LOS (P = 0.0001), occurrence of acute atrial fibrillation (AAF) (P = 0,039), and the following first postoperative day (FPD) variables: higher serum levels of creatinine (HSLC) (P < 0.003), fluid imbalance (FI) (P = 0,001), Nor-adrenaline tritation >0.1 μg/kg/min (Nor >0.1) and length of stay (LOS) in mechanical ventilation (MV) (P = 0.012).

Conclusion

In our sample using preoperative, peroperative and postoperative variables, we had only three preoperative markers of HHC (PH, ILAD, UAPA) and eight peroperative or postoperative (IAB, admission SICU BL, HSLC FPD, FI in FPD, FPD Nor >0.1, LOS in MV, SICU LOS and AAF). We interestingly showed that in hospital with our characteristics (high risk and urgency HS) it is difficult to predict HHC with only preoperative variables. We will need further step by step (pre, per and FPD) data analysis to format a predictive HHC for HS.