Collecting, evaluating and managing evidence is the most crucial part of research that drives policy and regulates medical technologies, and Systematic Reviews are the cornerstone of evidence-based research. A Systematic Review may contain tens of thousands of articles and papers and each of them may contain hundreds of data points. Given the growing volume of literature available for reviewers, using traditional methods to conduct Systematic reviews can be taxing.
Research conducted needs to be auditable, reproducible and stand up to scrutiny by relevant departments or Regulatory Bodies. Adding on to this, reviews are usually conducted on strict budgets, so reviewers need to be mindful of avoiding duplicate work or errors which may prove costly for the organization.
To overcome the above challenges, libraries, medical journals and experts swear by setting up a protocol to define the rationale, hypothesis, and methods of the project before the review has begun to streamline your systematic reviews. But how can you execute them in practice?
100% Configurable Workflows That Work The Way You Do
Systematic Reviews are generally conducted by teams which may consist of reviewers with varying levels of expertise working in collaboration, possibly from different geographical locations. Each department at every stage of product development has its own goals and workflows that address specific requirements. For example, the protocol at the discovery stage may have a protocol designed to identify opportunities in the market for a product while the Regulatory Affairs department may have one focused on obtaining necessary approvals from government agencies. Reviewing references yield better results when reviewers have clear, unambiguous instructions on where to start, what to include vs. exclude, and whom to engage.
To ensure reviewers in your organization are able to effectively collaborate in real time to screen, extract and present their error-free evidence in a standard report, automation is the way to go. According to Pulse of the Medical Devices Market Report, 73% of reviewers who use literature review software trust the quality of their data vs 37% who use spreadsheets, an error-prone, time consuming and resource intensive method. Here is how you can configure your protocol workflows and streamline your Systematic Review projects.
Setting Up Your Research Projects
When conducting a Systematic Review that has participants across geographical boundaries, reviewers need access to the right steps or levels and be able to see what needs to be done. It may sound simple, but when it comes to practicality, reviews done using spreadsheets are plagued by miscommunication, duplication of efforts and unclear project goals.
Your research protocol is a work plan, a step-by-step outline for knowledge synthesis. DistillerSR helps you bring your research protocol to life by easy configuration that is scalable and secure.
By setting up a project with well-planned levels, clearly defined inclusion and exclusion criteria, and assigning reviewers, you can eliminate all of the above challenges, arbitrary inclusion or elimination references,and any risk of bias. The non-linear workflow levels also helps avoid “screening fatigue” for reviewers. DistillerSR gives you the ability to easily configure even the most complex workflows that work for your organization.
Reviewers have ready access to the references they need to work on and DistillerSR takes care of the smooth transitioning of references across levels. Be it Dual Reviews, Conditional Workflows, Conflict Resolution or Quality Control operations, leave it to DistillerSR to manage it behind-the-scenes.
Reduce Your Literature Review Time By Half
AI-Powered Screening
Systematic Reviews by nature require a complete and exhaustive study of the current body of literature available on a topic which may sometimes be tens of thousands. Screening such a massive body of references takes up a significant portion of time in a systematic review. With the increasing volume of available references, it becomes an immense task which is laborious and time-consuming to not only thoroughly search a paper to identify relevant articles but also to do so correctly and prevent further delays.
DistillerSR helps you increase screening efficiency by stepping-in as a smart assistant. Using advanced Natural Language Processing, DistillerSR’s AI can learn your inclusion and exclusion pattern and automatically rearranges the reference set so that the more relevant ones are at the top, making it easier for you to include them.
DistillerSR’s AI can also detect duplicates even with different formatting, classify references for triaging and even check for references that may be erroneously excluded.
Efficient and Error-free Data Extraction
Spreadsheets have undeniably improved systematic reviews by enabling reviewers to digitally store, tabulate and share data. However, they still require extensive work, error-prone and essentially outdated. Any errors in data managed in spreadsheets are difficult to trace and rectify in a timely manner and hardly a step above manual methods.
“By learning my inclusion and exclusion pattern and reordering references based on relevance, DistillerSR’s AI enabled a more efficient overall review process and faster literature review completion rates.”
Shelley Jambresic, Senior Clinical Evaluation Manager at Geistlich Pharma AG
Data extraction with DistillerSR on the other hand, is strengthened by high configurability, extensive audit log, and version control providing the necessary stability and trustability. Reviewers can preemptively avoid transcription errors and the data is easily auditable. CuratorCR, a module of DistillerSR, provides reviewers with access to full-texts that were already purchased by the organization and to previously collected data that can be reused in the current project. This tremendously improves data quality and consistency apart from helping you save time and reducing costs.
Auto-generated PRISMA 2020 Flow-Diagram
Another DistillerSR advantage for your Systematic Review projects is the PRISMA 2020 Flow Diagram. It provides users the ability to automatically generate their PRISMA flow diagrams and its calculated numbers based on the decisions made and captured when using DistillerSR to conduct their screening. The most comprehensive and highly configurable PRISMA 2020 flow diagram is generated at the click of a button, saving you several days of work.
Conclusion
Automating your review process offers extensive benefits to reviewers. It helps you conduct smarter reviews that are transparent, audit-ready, and regulatory-compliant. If you want to achieve dramatically improved efficiencies in your Systematic Reviews, Request a Free Demo and see how DistillerSR can be easily configured to your preferred systematic review type.
DistillerSR® Inc. is the market leader in AI-enabled literature review automation software and creator of DistillerSR™. More than 300 of the world’s leading research organizations, including over 60 percent of the largest pharmaceutical and medical device companies, trust DistillerSR to securely produce transparent, audit-ready and regulatory compliant literature reviews faster and more accurately than any other method. With more organizations using DistillerSR to automate their systematic reviews, healthcare researchers can make informed and time-sensitive health policy decisions, clinical practice guidelines and regulatory submissions, and deliver better overall research.
