The Impact of Insurance Status on the Outcomes after Aneurysmal Subarachnoid Hemorrhage

Investigation into the association of insurance status with the outcomes of patients undergoing neurosurgical intervention has been limited: this is the first nationwide study to analyze the impact of primary payer on the outcomes of patients with aneurysmal subarachnoid hemorrhage who underwent endovascular coiling or microsurgical clipping. The Nationwide Inpatient Sample (2001–2010) was utilized to identify patients; those with both an ICD-9 diagnosis codes for subarachnoid hemorrhage and a procedure code for aneurysm repair (either via an endovascular or surgical approach) were included. Hierarchical multivariate regression analyses were utilized to evaluate the impact of primary payer on in-hospital mortality, hospital discharge disposition, and length of hospital stay with hospital as the random effects variable. Models were adjusted for patient age, sex, race, comorbidities, socioeconomic status, hospital region, location (urban versus rural), and teaching status, procedural volume, year of admission, and the proportion of patients who underwent ventriculostomy. Subsequent models were also adjusted for time to aneurysm repair and time to ventriculostomy; subgroup analyses evaluated for those who underwent endovascular and surgical procedures separately. 15,557 hospitalizations were included. In the initial model, the adjusted odds of in-hospital mortality were higher for Medicare (OR 1.23, p<0.001), Medicaid (OR 1.23, p<0.001), and uninsured patients (OR 1.49, p<0.001) compared to those with private insurance. After also adjusting for timing of intervention, Medicaid and uninsured patients had a reduced odds of non-routine discharge (OR 0.75, p<0.001 and OR 0.42, p<0.001) despite longer hospital stays (by 8.35 days, p<0.001 and 2.45 days, p = 0.005). Variations in outcomes by primary payer–including in-hospital post-procedural mortality–were more pronounced for patients of all insurance types who underwent microsurgical clipping. The observed differences by primary payer are likely multifactorial, attributable to varied socioeconomic factors and the complexities of the American healthcare delivery system.     

The Optimal Solution of a Non-Convex State-Dependent LQR Problem and Its Applications

This paper studies a Non-convex State-dependent Linear Quadratic Regulator (NSLQR) problem, in which the control penalty weighting matrix in the performance index is state-dependent. A necessary and sufficient condition for the optimal solution is established with a rigorous proof by Euler-Lagrange Equation. It is found that the optimal solution of the NSLQR problem can be obtained by solving a Pseudo-Differential-Riccati-Equation (PDRE) simultaneously with the closed-loop system equation. A Comparison Theorem for the PDRE is given to facilitate solution methods for the PDRE. A linear time-variant system is employed as an example in simulation to verify the proposed optimal solution. As a non-trivial application, a goal pursuit process in psychology is modeled as a NSLQR problem and two typical goal pursuit behaviors found in human and animals are reproduced using different control weighting . It is found that these two behaviors save control energy and cause less stress over Conventional Control Behavior typified by the LQR control with a constant control weighting , in situations where only the goal discrepancy at the terminal time is of concern, such as in Marathon races and target hitting missions.