Background: Sepsis research is limited by heterogeneity and inaccuracy of patient identification. An ideal identification algorithm would broadly define a population with suspected infection to optimize discrimination and provide real-time identification of high-risk populations for potential interventions. We combined clinical and administrative to identify a population of adults hospitalized with suspected infection and examined characteristics [...]