Dynamic Abandon/Extract Decisions for Failed Cardiac Leads

When a cardiac lead fails, physicians implant a new lead and may opt to extract the failed lead and/or any previously abandoned leads. Because the risk of extraction increases in lead age, physicians may extract leads to reduce the future risk of mandatory extraction, due to either infection or limited space in the vein. We develop discrete-time semi-Markov decision process models for various types of cardiac devices to determine patient-specific, lifetime-maximizing extraction policies as a function of patient age and the age of every implanted lead. We use clinical data to calibrate these models and present insightful numerical results, including comparisons to policies commonly used in practice. Our numerical experiments suggest that extracting failed leads only when forced to because of space limitations is usually a good rule of thumb, but that following the optimal policy, as opposed to the commonly used heuristic policies, can extend an average patient’s expected lifetime by up to 1.2 years and decrease the likelihood of device-related death by up to 94% in some cases.

The online appendix is available at https://doi.org/10.1287/mnsc.2016.2621.

This paper was accepted by Noah Gans, stochastic models and simulation.