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Minimally Invasive Thumb-sized Pterional Craniotomy for Surgical Clip Ligation of Unruptured Anterior Circulation Aneurysms
Published on: August 11, 2015
A predictive model of hospitalization cost after cerebral aneurysm clipping
Kimon Bekelis1, Symeon Missios2, Todd A MacKenzie3
1Section of Neurosurgery, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA.
Insights
This study identified key cost drivers for cerebral aneurysm clipping (CAC) hospitalizations. A predictive model was developed to aid in cost containment and policy creation for this neurosurgical procedure.
Area of Science:
- Neurosurgery
- Health Economics
- Health Services Research
Background:
- Cost containment is central to healthcare reform initiatives like the Affordable Care Act.
- Previous research has compared costs of cerebral aneurysm clipping (CAC) versus coiling, but lacked focus on CAC cost drivers and prediction.
- Understanding and predicting hospitalization costs after CAC is crucial for effective resource management.
Purpose of the Study:
- To develop and validate a predictive model for hospitalization costs associated with cerebral aneurysm clipping (CAC).
- To identify significant drivers influencing the cost of care for patients undergoing CAC.
Main Methods:
- A retrospective analysis of the Nationwide Inpatient Sample (NIS) database (2005-2010) was conducted.
- Patients undergoing CAC were divided into ruptured and unruptured aneurysm cohorts.
- Regression techniques were employed to build and validate a predictive cost model using derivation and validation subsamples.
Main Results:
- The study included 7798 patients undergoing CAC, with 58% for unruptured and 42% for ruptured aneurysms.
- Median hospitalization costs were $24,398 for unruptured and $73,694 for ruptured aneurysms.
- Key cost drivers identified included length of stay, number of diagnoses/procedures, hospital characteristics (size, region), and patient income. The predictive model showed good correlation between predicted and observed costs in validation cohorts.
Conclusions:
- Significant drivers of hospitalization cost following cerebral aneurysm clipping (CAC) were identified.
- The developed predictive model can support cost containment efforts and inform data-driven healthcare policies related to CAC.
Background:
Cost containment is the cornerstone of the Affordable Care Act. Although studies have compared the cost of cerebral aneurysm clipping (CAC) and coiling, they have not focused on identification of drivers of cost after CAC, or prediction of its magnitude. The objective of the present study was to develop and validate a predictive model of hospitalization cost after CAC.
Methods:
We performed a retrospective study involving CAC patients who were registered in the Nationwide Inpatient Sample (NIS) database from 2005 to 2010. The two cohorts of ruptured and unruptured aneurysms underwent 1:1 randomization to create derivation and validation subsamples. Regression techniques were used for the creation of a parsimonious predictive model.
Results:
Of the 7798 patients undergoing CAC, 4505 (58%) presented with unruptured and 3293 (42%) with ruptured aneurysms. Median hospitalization cost was US$24,398 (IQR $17,079 to $38,249) and $73,694 (IQR $46,270 to $115,128) for the two cohorts, respectively. Common drivers of cost identified in the multivariate analyses included the following: length of stay, number of admission diagnoses and procedures, hospital size and region, and patient income. The models were validated in independent cohorts and demonstrated final R(2) values very similar to the initial models. The predicted and observed values in the validation cohort demonstrated good correlation.
Conclusions:
This national study identified significant drivers of hospitalization cost after CAC. The presented model can be utilized as an adjunct in the cost containment debate and the creation of data driven policies.
