Abstract
Dashboards are data-driven clinical decision support tools used to analyze data from multiple databases using easy-to-read, color-coded graphical displays, much like the dashboards of automobiles. Dashboards can be used to promote data-driven decision making and improve adherence to evidence-based practice guidelines. The purpose of this article was to provide a review of dashboards used to query electronic health records for the purpose of guiding clinical practice and research. An inductive content analysis approach was used to identify emerging themes directly from the literature. Five basic dashboard properties identified include the type of database integration, visual properties, purpose, time focus (ie, retrospective, real time, or predictive), and type of process monitored. These dashboard properties are determined by the characteristics of the specific organization, user, and purpose of data analysis. Using dashboards to perform automated analytical reviews of clinical data will prove more efficient when data elements stored in electronic health records become standardized. Other limitations of dashboard use include user anxiety, information overload, and technology overload. The increased use of electronic documentation in healthcare settings will provide a wealth of data, and dashboards will play a pivotal role in converting these data into actionable knowledge.