We sought to determine whether a data-driven scheduling approach improves Operative Suite (OS) efficiency. Although efficient use of the OS is a critical determinant of access to health care services, OS scheduling methodologies are simplistic and do not account for all the available characteristics of individual surgical cases. We randomly scheduled cases in a single OS by predicting their length using either the historical mean (HM) duration of the most recent 4 years; or a regression modeling (RM) system that accounted for operative and patient characteristics. The primary endpoint was the imprecision in prediction of the end of the operative day. Secondary endpoints included measures of OS efficiency; personnel burnout captured by the Maslach Burnout Inventory; and a composite endpoint of 30-day mortality, myocardial infarction, wound infection, bleeding, amputation, or reoperation. Access Full Article.