Pross, ChristophStrumann, ChristophGeissler, AlexanderHerwartz, HelmutKlein, Nadja2018-09-132018-09-132018-09-06https://depositonce.tu-berlin.de/handle/11303/8184http://dx.doi.org/10.14279/depositonce-7339We specify a Bayesian, geoadditive Stochastic Frontier Analysis (SFA) model to assess hospital performance along the dimensions of resources and quality of stroke care in German hospitals. With 1,100 annual observations and data from 2006 to 2013 and risk-adjusted patient volume as output, we introduce a production function that captures quality, resource inputs, hospital inefficiency determinants and spatial patterns of inefficiencies. With high relevance for hospital management and health system regulators, we identify performance improvement mechanisms by considering marginal effects for the average hospital. Specialization and certification can substantially reduce mortality. Regional and hospital-level concentration can improve quality and resource efficiency. Finally, our results demonstrate a trade-off between quality improvement and resource reduction and substantial regional variation in efficiency.en610 Medizin und Gesundheitstochastic frontier analysishealth systemhospital performanceArticle1932-6203