As healthcare becomes an increasingly large sector of global economies, the need for accurate assessment of productivity and efficiency also increases. Hospitals are an important unit of analysis since they alone account for 1/3 to 1/2 of all healthcare spending in OECD countries. This presentation begins with an introduction to the two methods most commonly used to assess hospital performance in the academic literature, data envelopment analysis and stochastic frontier analysis. We discuss how the advantages of these methods can be blended, and present extensions to account for the comprehensive nature of quality in hospital production. To demonstrate, we combine three data sets (AHRQ National Inpatient Sample, CMS Hospital Cost Report Information System, CMS Hospital Compare) consisting of U.S. hospitals to obtain the most relevant input, output, and quality data related to hospital services.