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

Abstract

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 life-time cost-effectiveness of stroke care interventions. To develop a long-term model consisting of a set of equations to estimate the life-time effects of stroke care interventions to promote consistency in extrapolation of short-term outcomes. Data about further admissions and mortality was 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 life-time risk of mortality and secondary care resource utilisation including ED attendances, non-elective admissions, and elective admissions. A cohort of 1,509 (male 51%; mean age 74) stroke patients had median follow-up of seven years and represented 7,111 post-discharge patient years. A logistic model estimated mortality within twelve months of discharge and a Gompertz model was used over the remainder of the lifetime. Hospital attendances were modelled using a Weibull distribution. Non-elective and elective bed days were both modelled using a log-logistic distribution. Mortality risk increased with age, dependency, and male sex. Although the overall pattern was similar for resource utilisation, 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 discharge mRS of 1 would gain an extra 6.75 life years compared to 65-year-old women with a discharge mRS of 3. Over their lifetime, 65-year-old women with a discharge mRS 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 a discharge mRS of 3. Using long-term follow-up publicly available data from a large clinical cohort, this new model promotes standardised 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 is available upon reasonable request from third parties.