The Cost-Effectiveness of Real-Time Pulmonary Artery Pressure Monitoring in Heart Failure Patients: A European Perspective

Figure 1. State transition diagram. The Markov model has two health states, stable heart failure (HF) and death. There is a monthly transition probability of moving from stable HF to dead state. Hospitalization is modelled as an event; there is a monthly risk of patients being hospitalized, which is used to estimate the costs/quality‐adjusted life years. The patients are assumed to revert back to stable HF after hospitalization.

Figure 2. Survival curve showing the number of patients alive in the model over time. At 5 years, when the mortality effect from CHAMPION is removed from the model, the mortality rate increases. PAP, pulmonary artery pressure.

Figure 3. Cost‐effectiveness scatter plot. Each of the dots on the scatter plot is one of 1000 mean cost and utility results of 20 000 model runs each with different input values sampled from the input distributions. PAP, pulmonary artery pressure; WTP, willingness to pay. The WTP = £20 000/QALY (quality‐adjusted life year) is the typically accepted NICE (National Institute for Health and Care Excellence) threshold. Almost all of the samples (97.6%) fall under the WTP threshold, suggesting that CardioMEMS has a 97.6% probability of being cost‐effective at that threshold.

Figure 4. One‐way sensitivity analysis. The results of the sensitivity analysis can be compared in this tornado diagram; a larger bar indicates a greater impact on the incremental cost‐effectiveness ratio (ICER) or, in the case of mortality, indicates a wide range of uncertainty. The dotted line indicates the base case ICER. In the case of increased heart failure (HF) hospitalization costs the ICER is lower. HR, hazard ratio.