A Schematic Simulation for Health Economic Feasibility Studies: Results from a Model for Cardiac Remote Monitoring

The market for active implants and biosensors is of high economic and medical interest. As health economic considerations get into focus in terms of business planning and reimbursement, valid and flexible economic feasibility studies get more important. Unfortunately, literature mostly provides only single economic views on specific aspects like cost savings from reduced rehabilitation in a special patient cohort. To make planning and technology value negotiation more effective and more valid, a methodology to collect relevant data from different studies and normalize it to a common set of parameters was developed for the field of cardiac monitoring in a mixed example population with an approach of simple external weight, ECG and blood-pressure measurement or implanted devices for cardiac monitoring. The target entities taken into account by the simulation model were the impacts on heart attack, stroke, heart failure and the process of implant monitoring. Simulation took place at an example population of 500 patients with specific morbidity criteria. The health economic value was calculated over a period of three years and was split into a technology effectiveness measurement in Quality-adjusted-Lifetime-Years (QALYs) and a “cost- saving-part”. QALYs were chosen as technology effectiveness parameter for a combined and weighted mortality- and morbidity-reduction. Allocating 24.000 Euro to a saved QALY, 42% of the cost would be allocated to QALYs meaning money being spent for gained lifetime-years. The remaining 58% would be the different real cost savings: a per patient gross saving of 3.308 € per year would result for that part (21% on heart attack, 3% on stroke, 68% on heart failure and 8% on implant monitoring). Up-to-date studies do not provide a simple mechanism to allow custom-tailored health economic feasibility study results in terms of other specific population mixes or outcome parameters. Target audiences for the methodology of the described simulation are payors and solution providers targeting a specific patient population or specific telemedical situations. This way product development can address market-related needs more specific and healthcare providers can compare different outcome parameters in the given entities.