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.
Keywords: cost-effectiveness analysis; endovascular aneurysm repair (EVAR); health technology assessment (HTA); learning curve.
© 2017 The Authors. Health Economics published by John Wiley & Sons, Ltd.