Avoidable costs of stenting for aortic coarctation in the United Kingdom: an economic model

Abstract

Background: Undesirable outcomes in health care are associated with patient harm and substantial excess costs. Coarctation of the aorta (CoA), one of the most common congenital heart diseases, can be repaired with stenting but requires monitoring and subsequent interventions to detect and treat disease recurrence and aortic wall injuries. Avoidable costs associated with stenting in patients with CoA are unknown.

Methods: We developed an economic model to calculate potentially avoidable costs in stenting treatment of CoA in the United Kingdom over 5 years. We calculated baseline costs for the intervention and potentially avoidable complications and follow-up interventions and compared these to the costs in hypothetical scenarios with improved treatment effectiveness and complication rates.

Results: Baseline costs were £16 688 ($25 182) per patient. Avoidable costs ranged from £137 ($207) per patient in a scenario assuming a 10% reduction in aortic wall injuries and reinterventions at follow-up, to £1627 ($2455) in a Best-case scenario with 100% treatment success and no complications. Overall costs in the Best-case scenario were 90.2% of overall costs at Baseline. Reintervention rate at follow-up was identified as most influential lever for overall costs. Probabilistic sensitivity analysis showed a considerable degree of uncertainty for avoidable costs with widely overlapping 95% confidence intervals.

Conclusions: Significant improvements in the treatment effectiveness and reductions in complication rates are required to realize discernible cost savings. Up to 10% of total baseline costs could be avoided in the best-case scenario. This highlights the need to pursue patient-specific treatment approaches which promise optimal outcomes.

Keywords: Avoidable costs; Coarctation of the aorta; Congenital; Cost savings; Heart defects; Stents.

Fig. 1

Analytical approach and model structure illustrating alternative events and their sequelae. The primary outcome of this analysis is difference in costs between the Baseline scenario and four hypothetical scenarios of improved treatment effectiveness and patient safety. All scenarios include the same events at initial intervention, short-term, and mid-term follow-up. Scenarios differ in the probabilities attached to events. The figure shows possible events in the first period of the model (during or immediately after the initial intervention), and at short- and mid-term follow-up. The same events are included for short- and mid-term follow-up. Hypertension medication and imaging are not dependent on any other events and are therefore not connected to the other events. Hypertension is not directly influenced by other events at follow-up and does not impact on complications or reintervention rates itself. Imaging is recommended for all patients after CoA repair at least every two years [10]. Full circles indicate event probabilities subject to change in scenarios. Dotted circles indicate exogenous event probabilities

Fig. 2

Input probabilities for scenarios. Figure shows probabilities of events subject to change in the four scenarios compared to the Baseline scenario (red line). No bar shown for Best-case scenario for aortic wall injury; reintervention; and hypertension because the probability for these events is 0.0% in this scenario

Fig. 3

Tornado diagram

Fig. 4

Univariate sensitivity analysis for stenting success. The diagram shows the relationship between varying probabilities for treatment success (horizontal axis) and expected total costs compared to the initial input value (vertical axis) in Scenarios 1–3, as well as the Baseline scenario. Varying values of treatment success are displayed relative to the initial input (96.7% treatment success)

Fig. 5

Univariate sensitivity analysis for follow-up reinterventions. The diagram shows the relationship between varying probabilities for reinterventions at follow-up (horizontal axis) and expected total costs compared to the initial input value (vertical axis) in Scenarios 1–3, as well as the Baseline scenario. Varying values of reintervention rates are displayed relative to the initial input of 9.1% at short-term and 18.5% at mid-term follow-up

Fig. 6

Estimated avoidable costs in four scenarios; probabilistic sensitivity analysis. Blue circles represent mean expected avoidable costs compared to Baseline, with bars indicating 95% CIs. Red circles show estimates of the base-case analysis

Fig. 7

Estimated total costs; probabilistic sensitivity analysis. Results of PSA of total costs at Baseline and in four scenarios. Each circle represents expected total costs in one of n = 1000 iterations. Red bars show the mean result of iterations