Stroke treatment economic model (STEM) - Predicting long-term costs from functional status

被引:63
作者
Caro, JJ
Huybrechts, KF
机构
[1] Caro Res, Concord, MA 01742 USA
[2] McGill Univ, Royal Victoria Hosp, Div Gen Internal Med, Montreal, PQ H3A 1A1, Canada
关键词
costs and cost analysis; stroke; stroke outcome;
D O I
10.1161/01.STR.30.12.2574
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background and Purpose - Stroke is a debilitating disease with long-term with long-term social and economic consequences. As new therapies for acute ischemic stroke are forthcoming, there is an increasing need to understand their long-term economic implications. To address this need, a stroke economic model was created. Methods - The model consists of 3 modules. A short-term module incorporates short-term clinical trial data. A long-term module composed of several Markov submodels predicts patient transitions among various locations over time. The modules are connected via a bridge component that groups the survivors at the end of the short-term module according to their functional status and location. Examples of analyses that can be conducted with this model are provided with the use of data from 2 international trials. For illustration, UK unit costs were estimated. Results-With the trial data in the short-term module, the short-term management cost is estimated to be pound 8326 (US $13 649 [USD]). Hospital stay was the major cost driver. By the end of the trials, there was pronounced difference in the distribution of patient locations between functional groups. It is predicted in the long-term module that the subsequent cost amounts to pound 75 985 (124 564 USD) for a major and pound 27 995 (45 893 USD) for a minor stroke. Conclusions-Linking functional recovery at the end of short-term treatment with patients' treatment and residential locations allows this model to estimate the long-term economic impact of stroke interventions. Using patient location instead of the more common natural history as the model foundation allows quantification of the long-term impact to become data driven and hence increases confidence in the results.
引用
收藏
页码:2574 / 2579
页数:6
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