This research illustrates the state of the published evidence on the use of text-mining tools to support different systematic review processes and was conducted to provide the initial groundwork for future research into its utility to the systematic review community. To date, text-mining tools appear promising, but further research is warranted on: (1) actual costs, (2) actual workload reduction/time efficiencies, (3) whether its use is better suited to some types of review topics (e.g., well-defined clinical topics versus more diffuse public health topics), (4) when its use is most beneficial (e.g., is there enough added benefit for small result sets of <1,000 citations versus large result sets of >10,000 citations?), (5) development of evaluation metrics, and (6) head-to-head comparative performance evaluation of the tools themselves. Lastly, as these tools become more widely used in the review community, the need for clear reporting standards increases.