A Method to Account for Variation in Congenital Heart Surgery Length of Stay*

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Abstract

Objectives:

We sought to develop a risk-adjustment methodology for length of stay in congenital heart surgery, as none exist.

Design:

Prospective cohort analysis combined with previously obtained retrospective cohort analysis of a Department of Cardiovascular Surgery clinical database.

Patients:

Patients discharged from Boston Children’s Hospital between October 1, 2006, and May 31, 2014, that underwent a congenital heart surgery procedure(s) linked to one of 103 surgical procedure types.

Measurements and Main Results:

Six thousand two hundred nine discharges during the reporting period at Boston Children’s Hospital comprised the cohort. Seven Surgical Length Categories were developed to group surgical procedure types. A multivariable model for outcome length of stay was built using a derivation cohort consisting of a 75% random sample, starting with Surgical Length Categories and considering additional a priori factors. Postoperative factors were then added to improve predictive performance. The remaining 25% of the cohort was used to validate the multivariable models. The coefficient of determination (R2) was used to estimate the variability in length of stay explained by each factor. The Surgical Length Categories yielded an R2 of 42%. Model performance increased when the a priori factors preoperative status, noncardiac abnormality, genetic anomaly, preoperative catheterization during episode of care, weight less than 3 kg, and preoperative vasoactive support medication were introduced to the model (R2 = 60.8%). Model performance further improved when postoperative ventilation greater than 7 days, operating room time, postoperative catheterization during episode of care, postoperative reintubation, number of postoperative vasoactive support medications, postoperative ICU infection, and greater than or equal to one secondary surgical procedure were added (R2 = 76.7%). The validation cohort yielded an R2 of 76.5%.

Conclusions:

We developed a statistically valid procedure-based categorical variable and multivariable model for length of stay of congenital heart surgeries. The Surgical Length Categories and important a priori and postoperative factors may be used to pursue a predictive tool for length of stay to inform scheduling and bed management practices.

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