Sysrev provides more functionality than Covidence - at a fraction of the price.

Pricing

Sysrev is and will always be free for Public Projects. Public Projects are completely transparent reviews with findable, dedicated URLs that anybody can access (see a prostate cancer  review example).  

Sysrev supports private projects. PRO users can create unlimited private projects for $10/month. Team Pro allows teams to manage reviews together for $30/month. All private projects allow an unlimited number of reviewers.

Covidence charges per review: $240 for one or $445 for three. Each Covidence review can also have an unlimited number of reviewers.  

If you want to easily create dozens or hundreds of reviews Sysrev is the only reasonable option.  Sysrev user "roneal" has created 22 public projects - all for free. The math is simple. Sysrev is cheaper.  

Traditional Systematic Review

Sysrev is an incredibly flexible review platform. Almost everything Covidence does can be done on Sysrev.  To see a more detailed side-by-side feature comparison, check out Part 2 of this blog post.  

While we think Sysrev is always the stronger choice, if you are a Cochrane volunteer doing Cochrane style reviews you may want to stick with Covidence – which is the Cochrane supported application.  

Generalized Document Review

If you want to apply the systematic review process to a collection of non-academic articles Sysrev is a good choice.  You can create a review of any collection of PDFs by uploading a zip file.  Our wiki describes this in more detail.  Companies like SRG use pdf reviews to review safety data sheets (PDFs with data about chemical hazards).

Open Access Review

Sysrev is the only platform offering truly open access reviews like the NIEHS Cancer Hallmarks Review.  Researchers make their work more discoverable by creating free public - open access - Sysrev projects.

Public entities benefit from open access review by keeping their work more transparent and accessible to the public.  

Machine Learning

Sysrev is built around machine learning.  It aims to better integrate human and artificial intelligence.  Sysrev models already influence hundreds of public reviews.  Additionally, data generated during a Sysrev can be used to build your own machine learning models.  There is a tutorial for this at blog.sysrev.com/simple-ner.

Subscribe for an upcoming post about Sysrev's machine learning capabilities.  

Analytics Dashboard

Sysrev is rapidly developing an analytics dashboard to help project administrators gain insight into any potential issues with their reviewers or protocols.  You need an account to access it - but the dashboard is currently available for all public projects and is described in another blog post - blog.sysrev.com/user-inclusion-concordance/.

Accessible Auditing

Every reviewed article can be referenced with a link.  View an example from the Johns Hopkins liver effects project - link.

Linking to reviewed articles is an important part of auditing.  Simply share a link to see who reviewed which article, when they reviewed it, and what data was extracted. Links can also be used to view a subset of articles.  For example, this link shows all the 615 articles included in the Johns Hopkins liver toxicity review.  

API Integration

Sysrev is built for easy integration into other analytics programs.  Check out our github repos for python and R clients.  Blog.sysrev.com/simple-ner shows how Sysrev APIs can be used to build your own natural language processing models.  

Part 2 - Side-by-side Feature Comparison

As this post has shown, Sysrev is a powerful platform with many unique capabilities purposefully designed to help researchers conduct a wide variety of reviews.  To see a deeper dive into specific searching, screening, and extracting functionalities, check out Part 2 of this blog.