A systematic review of cost-effectiveness analyses on endovascular thrombectomy in ischemic stroke patients

A lifetime economic model of mortality and secondary care use for patients discharged from hospital following acute stroke

BACKGROUND

The long-term health-economic consequences of acute stroke are typically extrapolated from short-term outcomes observed in different studies, using models based on assumptions about longer-term morbidity and mortality. Inconsistency in these assumptions and the methods of extrapolation can create difficulties when comparing estimates of lifetime cost-effectiveness of stroke care interventions.

AIMS

To develop a long-term model consisting of a set of equations to estimate the lifetime effects of stroke care interventions to promote consistency in extrapolation of short-term outcomes.

METHODS

Data about further admissions and mortality were provided for acute stroke patients discharged between 2013 and 2014 from a large English service. This was combined with data from UK life tables to create a set of parametric equations in a model that use age, sex, and modified Rankin Scores to predict the lifetime risk of mortality and secondary care resource utilization including ED attendances, non-elective admissions, and elective admissions. A cohort of 1509 (male 51%; mean age 74) stroke patients had median follow-up of 7 years and represented 7111 post-discharge patient years. A logistic model estimated mortality within 12 months of discharge, and a Gompertz model was used over the remainder of the lifetime. Hospital attendances were modeled using a Weibull distribution. Non-elective and elective bed days were both modeled using a log-logistic distribution.

RESULTS

Mortality risk increased with age, dependency, and male sex. Although the overall pattern was similar for resource utilization, there were different variations according to dependency and gender for ED attendances and non-elective/elective admissions. For example, 65-year-old women with a mRS at discharge of 1 would gain an extra 6.75 life years compared to 65-year-old women with a mRS at discharge of 3. Over their lifetime, 65-year-old women with an mRS at discharge of 1 would experience 0.09 less ED attendances, 2.12 less non-elective bed days, and 1.28 additional elective bed days than 65-year-old women with an mRS at discharge of 3.

CONCLUSIONS

Using long-term follow-up publicly available data from a large clinical cohort, this new model promotes standardized extrapolation of key outcomes over the life course and potentially can improve the real-world accuracy and comparison of long-term cost-effectiveness estimates for stroke care interventions.

DATA ASSESS STATEMENT

Data are available upon reasonable request from third parties.

Lifetime economic potential of mobile stroke units in acute stroke care: A model-based analysis of the drivers of cost-effectiveness

BACKGROUND AND PURPOSE

To simulate patient-level costs, analyze the economic potential of telemedicine-based mobile stroke units for acute prehospital stroke care, and identify major determinants of cost-effectiveness, based on two recent prospective trials from the United States and Germany.

METHODS

A Markov decision model was developed to simulate lifetime costs and outcomes of mobile stroke unit. The model compares diagnostic and therapeutic pathways of ischemic stroke, hemorrhagic stroke, and stroke mimic patients by conventional care or by mobile stroke units. The treatment outcomes were derived from the B_PROUD and the BEST-mobile stroke unit trials and further input parameters were derived from recent literature. Uncertainty was addressed by deterministic and probabilistic sensitivity analyses. A lifetime horizon based on the US healthcare system was adopted to evaluate different cost thresholds for mobile stroke unit and the resulting cost-effectiveness. Willingness-to-pay thresholds were set at 1x and 3x gross domestic product per capita, as recommended by the World Health Organization.

RESULTS

In the base case scenario, mobile stroke unit care yielded an incremental gain of 0.591 quality-adjusted life years per dispatch. Mobile stroke unit was highly cost-effective up to a maximum average cost of 43,067 US dollars per patient. Sensitivity analyses revealed that MSU cost-effectiveness is mainly affected by reduction of long-term disability costs. Also, among other parameters, the rate of stroke mimics patients diagnosed by MSU plays an important role.

CONCLUSION

This study demonstrated that mobile stroke unit can possibly be operated on an excellent level of cost-effectiveness in urban areas in North America with number of stroke mimic patients and long-term stroke survivor costs as major determinants of lifetime cost-effectiveness.