Fact Sheet

Health economics and outcomes research (HEOR) scientists are under increased pressure to produce higher-quality results faster and at lower costs while confronting the rising tide of research data. In many HEOR fields, decision-making and policy development happen concurrently with the publication of results, making it even more difficult to organize and analyze large volumes of evidence.

With DistillerSR, HEOR scientists can conduct transparent and reproducible literature reviews faster and more accurately by leveraging AI-powered automation, intelligent workflows, and data reuse.

Automate many of the traditional review tasks so you can produce work quickly, accurately, and cost-effectively.

By using auto-alerts from data providers such as PubMed, EBSCO, and Ovid, DistillerSR allows you to automatically update reviews with new references as soon as they become available. Time spent rerunning searches is eliminated and living reviews are always up to date with new references.

Freely available full-text documents can be automatically retrieved and added to systematic reviews. Review teams can leverage their Article Galaxy and RightFind subscriptions to order full-text documents from within DistillerSR for the lowest possible cost.

Connect directly to source materials stored in your organization’s eLibrary and through DOI.org. This eliminates the tedious task of searching for and uploading full-text documents.

By enabling reviewers to sift through large volumes of references with the help of AI, DistillerSR allows you to find what you need quickly.

Using powerful duplicate detection built within your workflow, DistillerSR easily identifies and removes duplicate records. The literature review software also automatically tracks their removal for standard reporting and preserves them for future reference and retrieval.

With the help of AI, DistillerSR allows you to quickly find what you need and easily sort through irrelevant materials. Its AI differentiates between relevant and irrelevant records, continuously reprioritizing the remaining, as-yet-unscreened records, and then presents them based on the likelihood of relevance.

On average, you can find most of your relevant references 40–60% sooner than conventional screening.

Confirm that you haven’t accidentally excluded any relevant references. DistillerSR’s AI double- checks your exclusions for errors, increasing your confidence in your screening decisions. Conflicts and disagreements between reviewers, meanwhile, are automatically identified and set aside for easy resolution.

DistillerSR lets you define your preferred workflows. This enables you to streamline and improve the quality of your reviews, follow best practices and methodologies, and reduce logistical overhead for local and global teams.

Extract, appraise, and report data in a way that fits your protocol. Furthermore, when you need to conduct similar research, you can instantly reuse your review process across multiple reviews by creating templates. These can be copied and modified as needed.

Reduce human error by requiring data validation at the time of extraction, for example by using prespecified acceptable ranges for numerical values. Configured to meet your requirements, DistillerSR’s in-form data validation lets your team spend less time and effort acquiring analysis-ready data.

You can also easily follow globally recognized standards and compliance requirements. This includes auto-generating PRISMA flow diagrams, maintaining strict version control, and producing fully transparent and audit-ready results.

DistillerSR facilitates a transparent process that tracks all project and account activity. In addition, it provides insights for the intelligent and automated management of your literature review processes.

DistillerSR tracks all review activity and makes it easy to view the provenance of every cell of data. You can restrict access and ensure your data meets your organization’s security standards through single sign-on (SSO) and user permissions.

Distributed teams can collaborate more effectively, with standard processes in place and reduced management overhead. Reviewers are automatically assigned and notified of new work — regardless of the number of projects they’re working on. Project managers can view real-time user and project metrics to gain insight into the team’s workload, participation, quality, and performance.

Scheduled reports can be configured and sent to you (and your stakeholders) automatically via email. Reports can be configured based on rolling date ranges and distributed at specific time intervals. This capability gives you the flexibility to track and share what’s important in the progress of your review.

DistillerSR’s CuratorCR module automatically notifies you if anyone in your organization has already collected data for a reference. This increases overall review efficiency as citations are linked to existing extracted data and can be reused for other projects.

CuratorCR eliminates unnecessary duplication of effort by easily finding, viewing, validating, and reusing already collected data and PDFs across reviews and teams.

Regardless of the subject matter, the size of your team, or how many reviews you have on the go, DistillerSR gives you the tools and flexibility you need to create a reliable, transparent, and fully reproducible process.