Varabyova Yauheniya, Blankart Carl Rudolf, Schreyögg Jonas
Hamburg Center for Health Economics, Universität Hamburg, Hamburg, Germany.
Center for Gerontology and Health Care Research, School of Public Health, Brown University, Providence, RI, USA.
Health Econ. 2017 Feb;26 Suppl 1:93-108. doi: 10.1002/hec.3466.
Changes in performance due to learning may dynamically influence the results of a technology evaluation through the change in effectiveness and costs. In this study, we estimate the effect of learning using the example of two minimally invasive treatments of abdominal aortic aneurysms: endovascular aneurysm repair (EVAR) and fenestrated EVAR (fEVAR). The analysis is based on the administrative data of over 40,000 patients admitted with unruptured abdominal aortic aneurysm to more than 500 different hospitals over the years 2006 to 2013. We examine two patient outcomes, namely, in-hospital mortality and length of stay using hierarchical regression models with random effects at the hospital level. The estimated models control for patient and hospital characteristics and take learning interdependency between EVAR and fEVAR into account. In case of EVAR, we observe a significant decrease both in the in-hospital mortality and length of stay with experience accumulated at the hospital level; however, the learning curve for fEVAR in both outcomes is effectively flat. To foster the consideration of learning in health technology assessments of medical devices, a general framework for estimating learning effects is derived from the analysis. © 2017 The Authors. Health Economics published by John Wiley & Sons, Ltd.
由于学习导致的性能变化可能会通过有效性和成本的变化动态影响技术评估的结果。在本研究中，我们以腹主动脉瘤的两种微创治疗方法为例估计学习效应：血管内动脉瘤修复术（EVAR）和开窗型血管内动脉瘤修复术（fEVAR）。该分析基于2006年至2013年期间500多家不同医院收治的40000多名未破裂腹主动脉瘤患者的管理数据。我们使用医院层面具有随机效应的分层回归模型来研究两个患者结局，即住院死亡率和住院时间。估计模型控制了患者和医院特征，并考虑了EVAR和fEVAR之间的学习相互依赖性。对于EVAR，我们观察到随着医院层面经验的积累，住院死亡率和住院时间均显著下降；然而，fEVAR在这两个结局方面的学习曲线实际上是平坦的。为了促进在医疗设备的卫生技术评估中考虑学习效应，我们从分析中得出了一个估计学习效应的通用框架。© 2017作者。《健康经济学》由约翰·威利父子有限公司出版。
