Optimal Implantable Cardioverter Defibrillator (ICD) Generator Replacement

Implantable cardioverter defibrillators ( ICDs) include small, battery-powered generators, the longevity of which depends on a patient's rate of consumption. Generator replacement, however, involves risks, including death. Hence, a trade-off exists between prematurely exposing the patient to these risks and allowing for the possibility that the device is unable to deliver therapy when needed. Currently, replacements are performed using a one-size-fits-all approach. Here, we develop a Markov decision process model to determine patient-specific optimal replacement policies as a function of patient age and the remaining battery capacity. We analytically establish that the optimal policy is of threshold-type in the remaining capacity, but not necessarily in patient age. Based on clinical data, we conduct a large computational study that suggests that under the optimal policy, patients undergoing initial implantation at age 30-40, 41-60, and 61-80 see an approximate decrease in the total expected number of replacements of 8%-14%, 8%-15% and 8%-19%, respectively, while achieving the same or greater expected lifetime.