Over the last 15 years, evidence has been accumulating relating higher levels of nurse staffing in both quantity and experience to lower rates of adverse patient outcomes. Consequently, to promote quality patient outcomes efficiently, making staffing decisions based in evidence is of increasing importance. However, there is still limited data to help decide how to effectively allocate scarce nurse resources in practice. Existing principles, frameworks, and guidelines provide a foundation for nurse staffing decisions but face poor adoption. To determine optimal nurse staffing practices and provide evidence-based recommendations for policy, and integration into operations, comprehensive data are necessary. Information technology can assist nurse staffing decisions. Four informatics processes that may support evidence-based nurse staffing are described: (a) Data acquisition from multiple data sources, (b) Representation of data in a way it can be re-used for multiple purposes, (c) Sophisticated data processing and mining, and (d) Presentation of data in standardized and user-configurable ways.