Network meta-analysis (NMA) is a powerful analysis method used to identify the best treatments for a condition that is used extensively by healthcare decision makers. Although software routines exist for conducting NMAs, they require considerable statistical programming expertise to use, which limits the number of researchers able to conduct such analyses.
To develop a web-based tool allowing users with only standard internet browser software to be able to conduct NMAs using an intuitive ‘point and click’ interface and present the results in as visual and appealing way as possible.
Using the existing netmeta and Shiny packages for R to conduct the analyses, and to develop the user interface, together with our own innovations for presenting the results, we created the MetaInsight tool which is freely available to use via any internet browser.
We created a package for conducting NMA of both continuous and binary outcomes, which satisfied our objectives. This is described, and its application demonstrated, using an illustrative example of a mixed treatment comparison of pharmacological interventions for the treatment of obesity.
We believe many researchers will find our package helpful for facilitating NMAs, as well as allowing decision-makers to scrutinize presented results visually and in real-time. This will have an impact on the quality of statistical analyses and healthcare decisions, and increase capacity sustainably by empowering informed non-specialists to be able to conduct more clinically relevant reviews.
Patient or healthcare consumer involvement:
Our user-friendly, interactive, web-based tool was designed to provide patients, health professionals and healthcare decision makers with the opportunity to explore datasets from systematic reviews, and scrutinize the robustness of analyses in real time. The tool empowers patients to ask subtle variations of the primary research question and explore the evidence base to support a personalized approach to health care. The interactive tool presents results in an intuitive, visually appealing, and user-friendly capacity, which will facilitate understanding and interpretation to help inform patient-clinician discussion.