Simulating Cardiac Fluid Dynamics in the Human Heart

Cardiac fluid dynamics fundamentally involves interactions between complex blood flows and the structural deformations of the muscular heart walls and the thin, flexible valve leaflets. There has been longstanding scientific, engineering, and medical interest in creating mathematical models of the heart that capture, explain, and predict these fluid-structure interactions. However, existing computational models that account for interactions among the blood, the actively contracting myocardium, and the cardiac valves are limited in their abilities to predict valve performance, resolve fine-scale flow features, or use realistic descriptions of tissue biomechanics. Here we introduce and benchmark a comprehensive mathematical model of cardiac fluid dynamics in the human heart. A unique feature of our model is that it incorporates biomechanically detailed descriptions of all major cardiac structures that are calibrated using tensile tests of human tissue specimens to reflect the heart's microstructure. Further, it is the first fluid-structure interaction model of the heart that provides anatomically and physiologically detailed representations of all four cardiac valves. We demonstrate that this integrative model generates physiologic dynamics, including realistic pressure-volume loops that automatically capture isovolumetric contraction and relaxation, and predicts fine-scale flow features. None of these outputs are prescribed; instead, they emerge from interactions within our comprehensive description of cardiac physiology. Such models can serve as tools for predicting the impacts of medical devices or clinical interventions. They also can serve as platforms for mechanistic studies of cardiac pathophysiology and dysfunction, including congenital defects, cardiomyopathies, and heart failure, that are difficult or impossible to perform in patients

Insurance Claim Operations: The Role of Economic Incentives

We develop a theory of insurance claim settlement whose structure embodies an insurer’s capacity decision and negotiation between the insurer and claimant in an asymmetrically informed environment. We offer a solution to an insurer’s choice of upfront claim settlement amount under a plausible set of assumptions. Implications from theory are tested with a large sample of liability insurance claims collected over two years in the state of Texas and we find that insurer’s deployment of more capacity to handle a claim and longer settlement times occur for claims with more uncertainty. The empirical results also reveal factors relevant to insurer’s operational choices. Descriptive features of a claim, the age of the claimant and attorney representation on the plaintiff’s side are important determinants of the final settlement amount