How to Use EPPI-Reviewer for Data Extraction and Synthesis

By Dr. Zubair Khalid, DVM, MS, PhD · 2026-08-27

Quick Answer

• EPPI-Reviewer supports systematic review data extraction through customizable coding tools, but the interface requires deliberate setup before efficient use.
• Begin by creating a review library, then build a structured data extraction form with clearly defined codes before importing any studies.
• The software handles both qualitative and quantitative synthesis, yet mastery depends on consistent coding practices and regular backup of your review file.

Understanding EPPI-Reviewer for Systematic Reviews

EPPI-Reviewer is a web-based software platform designed to support the entire systematic review process, from reference management through data extraction and evidence synthesis. Developed by the Evidence for Policy and Practice Information and Coordinating Centre at University College London, this tool serves researchers who need to manage large volumes of literature while maintaining transparency and reproducibility in their review methods.

The platform operates on a library-based structure where each review project exists as a separate entity containing all associated references, coding frameworks, and synthesis outputs. This architecture allows research teams to collaborate on shared projects while maintaining version control and audit trails. For researchers transitioning from traditional spreadsheet-based review methods, EPPI-Reviewer offers a more integrated approach that connects each stage of the review workflow.

Systematic reviews demand rigorous methodology because they synthesize evidence from multiple studies to answer specific research questions. The National Library of Medicine provides access to authoritative texts on research methodology that explain why structured approaches to evidence synthesis matter. When you use EPPI-Reviewer, you are implementing a structured framework that aligns with these established methodological principles.

The software distinguishes itself from general reference managers by focusing specifically on the review process. While tools like EndNote or Zotero help you collect and organize citations, EPPI-Reviewer adds layers of coding, quality assessment, and synthesis functionality that address the unique needs of systematic reviewers. This specialization means the learning curve differs from general-purpose tools, but the investment in learning pays dividends during data extraction and synthesis phases.

Core Principles of Data Extraction in EPPI-Reviewer

Data extraction in systematic reviews involves systematically collecting relevant information from each included study according to a predefined framework. EPPI-Reviewer operationalizes this through its coding system, which allows you to assign structured labels to segments of text or entire documents.

The coding framework in EPPI-Reviewer functions as your data extraction form. Each code represents a variable you want to capture from the studies in your review. These codes can be organized hierarchically, allowing you to create parent codes with nested subcodes that capture increasingly specific details. For example, a parent code for "study design" might contain subcodes for "randomized controlled trial," "cohort study," "qualitative interview," and other design categories.

Your coding framework should emerge directly from your research question and protocol. Before you begin extracting data, you need clarity about what information matters for answering your review question. The EQUATOR Network provides reporting guidelines that can help you identify which study characteristics and outcomes you should extract to ensure your review meets reporting standards.

Consistency in coding is essential for producing reliable synthesis results. When multiple reviewers extract data from the same studies, you need clear definitions for each code to minimize interpretation differences. EPPI-Reviewer supports this through its codebook feature, which lets you document the meaning and scope of each code within the software itself.

Setting Up Your Review Library

Creating a new review in EPPI-Reviewer begins with establishing your project structure. The software guides you through initial setup, where you name your review and provide basic metadata that identifies the project. This metadata becomes part of your review's audit trail, documenting when the review was created and who manages it.

After creating the review, you need to establish your coding framework before importing references. This sequencing matters because EPPI-Reviewer allows you to code studies as you screen them, and having your framework ready from the start prevents rework. You can modify codes later, but changes to the framework may require recoding previously processed studies.

The coding framework editor in EPPI-Reviewer lets you create codes through a straightforward interface. You assign each code a name and optional description that guides coders in applying it consistently. The hierarchical structure supports organizing codes into logical groups that mirror your extraction form's sections, such as study characteristics, participant information, intervention details, and outcome measures.

Your review library also stores the full text documents you will code. EPPI-Reviewer accepts PDF files and other document formats, allowing you to attach source files to their corresponding references. This integration means your coding work connects directly to the evidence, making it easier to verify extractions and revisit specific passages during synthesis.

Building a Data Extraction Form

A well-designed data extraction form captures all the information you need while remaining practical to apply across diverse studies. In EPPI-Reviewer, this form takes shape as your coding framework, with each code representing a field in your extraction template.

Start by listing the key variables your review must capture. These typically include bibliographic details, study aims, setting and context, participant characteristics, intervention or exposure details, comparison conditions, outcome measures, results, and author conclusions. Your research protocol should specify which of these variables matter for your particular review question.

For each variable, decide whether you need a simple categorical code, a free-text response, or a more complex coding structure. EPPI-Reviewer supports different code types that accommodate these varying needs. Categorical codes work well for study design classifications, while free-text codes allow you to record specific numerical results or verbatim quotes from studies.

The EQUATOR Network offers reporting guidelines that can inform your extraction form design. These guidelines specify what information should be reported for different study types, and you can use them as checklists when deciding which variables to extract. This approach ensures your extraction captures the elements needed for transparent reporting of your review.

Pilot testing your extraction form on a small sample of studies helps identify ambiguities or missing variables before you process your full set of included studies. This testing phase is a quality control step that reduces the likelihood of inconsistent coding across your review team.

Coding Studies for Data Extraction

Once your framework is ready and references are imported, you begin the coding process. EPPI-Reviewer presents each reference with its attached full text, allowing you to read the document and apply codes as you encounter relevant information.

The coding interface displays your code tree alongside the document viewer. You select text passages or the entire document and assign applicable codes. For categorical codes, you choose from predefined options. For free-text codes, you type your extraction directly into the software, with the option to link your entry to specific text in the source document.

Efficient coding requires a systematic approach. Read each study thoroughly before applying codes to ensure you capture all relevant information. Some reviewers prefer to code study characteristics first, then move through intervention details, outcomes, and other sections in a consistent order. This consistency helps prevent missed extractions and makes it easier to spot errors when you review your work.

EPPI-Reviewer tracks which codes have been applied to each reference, showing your progress through the extraction phase. This visibility helps you monitor completion and identify studies that may need additional attention. The software also supports double coding, where two reviewers independently code the same study, allowing you to assess inter-rater reliability.

Managing Multiple Reviewers and Consistency

Systematic reviews often involve teams of reviewers working on different studies or different aspects of the same studies. EPPI-Reviewer supports collaborative work through user accounts and permissions that control who can access and modify the review.

When multiple reviewers code studies, consistency becomes a primary concern. The Committee on Publication Ethics emphasizes the importance of transparent and reproducible research practices, and consistent coding is part of that transparency. EPPI-Reviewer provides tools to support consistency checking, including the ability to compare coding between reviewers and calculate agreement statistics.

Before full-scale extraction begins, conduct a calibration exercise where all reviewers code the same set of studies independently, then compare results. This exercise identifies codes that are being applied inconsistently and allows the team to refine definitions or provide additional training before processing the full set of studies.

During the extraction phase, schedule regular check-ins to discuss challenging coding decisions. Some studies will present ambiguous information that does not fit neatly into your predefined codes. Documenting these decisions and their resolutions creates a decision log that strengthens the transparency of your review process.

Using Synthesis Features for Evidence Synthesis

After completing data extraction, EPPI-Reviewer's synthesis features help you analyze and combine the extracted information to answer your research question. The software supports both quantitative and qualitative synthesis approaches, accommodating different review types.

For quantitative reviews, EPPI-Reviewer can export extracted data in formats compatible with statistical analysis software. This export capability allows you to perform meta-analysis using specialized tools while maintaining the connection between your extracted data and the original studies. The software also provides descriptive statistics that summarize the characteristics of included studies.

For qualitative reviews, EPPI-Reviewer supports thematic synthesis and other qualitative analysis approaches. You can use the coding structure to group findings across studies, identify patterns and themes, and explore relationships between study characteristics and reported outcomes. The software's ability to link codes to specific text passages means your synthesis remains grounded in the source evidence.

The synthesis process in EPPI-Reviewer is iterative. You may find that initial synthesis results reveal gaps in your extraction, requiring you to return to studies and apply additional codes. This flexibility is a strength of the software, allowing your analysis to evolve as you develop deeper understanding of the evidence.

Exporting Data and Creating Reports

EPPI-Reviewer provides multiple export options that support different downstream uses of your review data. Understanding these options helps you plan how your extracted data will feed into your final review report or other outputs.

The software can export your coding framework and applied codes in structured formats that preserve the relationships between codes and references. These exports are useful for creating appendices that document your extraction process, a practice that supports the transparency expectations outlined by the Committee on Publication Ethics.

For quantitative data, EPPI-Reviewer exports can be formatted for direct import into statistical packages. This integration reduces transcription errors that can occur when manually transferring data between systems. The exported data retains reference identifiers, allowing you to trace any data point back to its source study.

When preparing your final report, the EQUATOR Network guidelines help ensure you report your review methods and findings completely and transparently. Your EPPI-Reviewer project contains the audit trail that demonstrates how you conducted your review, from initial screening through final synthesis.

At a Glance

Practical Implementation Steps

Implementing EPPI-Reviewer for your systematic review requires a structured approach that begins before you import your first reference. Following a deliberate sequence helps you avoid common pitfalls and build a review project that supports efficient extraction and synthesis.

First, finalize your research question and protocol. Your protocol should specify your inclusion criteria, search strategy, and planned synthesis approach. This document becomes the foundation for your coding framework and guides all subsequent decisions in EPPI-Reviewer.

Second, create your review project and build your initial coding framework. Start with the variables you know you need based on your protocol, and plan to refine the framework after pilot testing. Include both categorical and free-text codes as appropriate for your review type.

Third, import your references and full texts. EPPI-Reviewer accepts standard reference formats and allows you to attach PDF files to references. Organize your screening process within the software so you can track which references have been screened and which have been excluded.

Fourth, pilot test your coding framework on a sample of included studies. This testing phase should involve all reviewers who will participate in extraction. Compare results, discuss discrepancies, and refine your code definitions before proceeding to full extraction.

Fifth, conduct your full extraction phase with regular consistency checks. Monitor progress through the software's tracking features and address any emerging questions promptly. Document all coding decisions that fall outside your predefined framework.

Sixth, move into synthesis once extraction is complete. Use EPPI-Reviewer's synthesis features to explore patterns in your extracted data, and export data as needed for additional analysis.

Records and Measurements

Maintaining accurate records throughout your EPPI-Reviewer project supports both the integrity of your review and your ability to report your methods transparently. The software automatically tracks certain information, but you should also maintain supplementary records that document your decision-making.

EPPI-Reviewer records which user applied each code and when, creating an automatic audit trail. This information is valuable for demonstrating the transparency of your review process, a principle emphasized by the Committee on Publication Ethics. Reviewers should be aware that their coding activities are logged and should ensure their work reflects careful, deliberate decisions.

Beyond the automatic records, maintain a decision log that documents challenges encountered during extraction and how they were resolved. This log should include dates, the studies involved, the nature of the challenge, and the resolution reached. Such documentation proves valuable when writing your methods section and if questions arise about your review process.

Track your progress through the extraction phase using EPPI-Reviewer's progress indicators. These measurements help you estimate remaining work and identify studies that may require additional attention. If you are working to a deadline, regular progress monitoring helps you adjust your workflow to stay on schedule.

Common Failure Patterns

Researchers using EPPI-Reviewer often encounter predictable challenges that can disrupt their review workflow. Recognizing these patterns helps you avoid them or address them quickly when they arise.

One common failure is building the coding framework without sufficient pilot testing. Reviewers who skip the pilot phase often discover that their codes do not capture important information or that code definitions are ambiguous when applied to real studies. This discovery typically happens after significant extraction work, requiring time-consuming recoding.

Another frequent issue is inconsistent coding across reviewers. Without calibration exercises and ongoing consistency checks, different reviewers may apply the same codes differently. This inconsistency compromises the reliability of your extracted data and can undermine the validity of your synthesis findings.

Some researchers struggle with the relationship between screening and extraction. EPPI-Reviewer allows coding during screening, but mixing these phases without clear procedures can lead to incomplete extraction or premature exclusion of studies. Maintaining clear separation between screening decisions and extraction activities helps preserve the integrity of both processes.

Data management failures also occur when reviewers do not regularly back up their review projects or when team members work on outdated versions. EPPI-Reviewer stores projects centrally, but you should still establish procedures for saving and version control to prevent data loss.

Limitations and Considerations

EPPI-Reviewer is a powerful tool, but it has limitations that researchers should understand before committing to its use. Being aware of these constraints helps you plan your review workflow appropriately and avoid frustration.

The software has a learning curve that can be steep for researchers accustomed to simpler tools. The interface presents many options and features, and mastering the workflow takes time. Budgeting for this learning period in your review timeline is essential, especially if your team has no prior EPPI-Reviewer experience.

EPPI-Reviewer's synthesis capabilities, while useful, may not replace specialized analysis software for all review types. Quantitative meta-analysis typically requires dedicated statistical software, and complex qualitative analysis may benefit from additional tools. Plan for how you will handle these analysis needs beyond what EPPI-Reviewer provides directly.

The software's collaborative features require all team members to have appropriate access and training. If your team includes members with varying technical proficiency, you may need to provide additional support to ensure consistent use of the platform.

Cost is another consideration. EPPI-Reviewer operates on a subscription model, and access may require institutional support. Researchers without institutional subscriptions should explore whether their organization can provide access or whether alternative tools better fit their circumstances.

Welfare and Safety Context

While EPPI-Reviewer itself does not directly involve animal welfare or safety concerns, systematic reviews in life sciences and animal-related fields must address these considerations in their research questions and data extraction frameworks.

If your review addresses animal studies, your extraction form should capture information about animal welfare standards, housing conditions, and ethical approvals. The National Library of Medicine provides access to research methodology texts that discuss considerations for reviews involving animal studies, including how to assess reporting quality and ethical compliance.

For reviews involving human participants, your extraction should capture information about informed consent, ethical approval, and participant safety. These elements are essential for assessing the quality and ethical conduct of included studies, and they should be part of your coding framework from the outset.

The National Institutes of Health provides guidance on responsible conduct of research that applies to the broader context of your review work. Ensuring your review process follows ethical principles, including transparent reporting and proper attribution, aligns with these expectations.

Professional Escalation Criteria

Knowing when to seek additional support or escalate issues is important for maintaining the quality of your systematic review. Several situations warrant consulting with colleagues, supervisors, or technical support.

If you encounter persistent technical problems with EPPI-Reviewer that interfere with your workflow, contact the software's technical support team. Document the issues you experience, including error messages and the steps you took, to facilitate efficient troubleshooting.

When coding decisions involve substantial ambiguity or disagreement among reviewers, escalate these issues to your review team lead or methodologist. Some coding challenges require methodological expertise to resolve appropriately, and attempting to resolve them without this input may compromise your review's validity.

If your review addresses a topic with significant safety or welfare implications, and you encounter studies with concerning findings, consider whether these findings warrant escalation to relevant authorities or ethics committees. Your responsibility extends beyond completing the review to considering the implications of what you find.

For reviews that will inform policy or practice decisions, involve stakeholders or content experts when synthesis findings have important implications. Their input can help ensure your interpretations are appropriate and your recommendations are actionable.

Frequently Asked Questions

How do I create a new review project in EPPI-Reviewer?

Log into EPPI-Reviewer and select the option to create a new review. You will provide basic information about your review, including its title and a brief description. After creating the project, you can begin building your coding framework and importing references.

What types of codes can I create in EPPI-Reviewer?

EPPI-Reviewer supports categorical codes with predefined options and free-text codes for open-ended responses. You can organize codes hierarchically, creating parent codes with nested subcodes. This structure allows you to capture both structured and unstructured information from your included studies.

Can multiple reviewers work on the same EPPI-Reviewer project?

Yes, EPPI-Reviewer supports collaborative work. Project administrators can add team members with appropriate permissions, allowing multiple reviewers to code studies and contribute to the review. The software tracks which user applied each code, supporting accountability and consistency assessment.

How do I export data from EPPI-Reviewer for statistical analysis?

EPPI-Reviewer provides export functions that format your extracted data for use in other software. You can export coding data in structured formats that preserve the relationships between codes and references. These exports can be imported into statistical packages for meta-analysis or other quantitative synthesis.

Does EPPI-Reviewer support qualitative synthesis methods?

Yes, EPPI-Reviewer supports qualitative synthesis approaches. You can use the coding structure to group findings across studies, identify themes, and explore patterns in qualitative data. The software maintains links between codes and source text, keeping your synthesis grounded in the evidence.

How should I handle coding disagreements between reviewers?

Address coding disagreements through discussion and consensus. If reviewers cannot resolve a disagreement, involve a third reviewer or your methodologist to make a final decision. Document all disagreements and their resolutions in your decision log for transparency.

Is EPPI-Reviewer suitable for rapid reviews or only full systematic reviews?

EPPI-Reviewer can support both rapid and full systematic reviews. The software's flexibility allows you to adapt your workflow to the scope and timeline of your review. For rapid reviews, you may streamline your coding framework and synthesis approach while still maintaining methodological rigor.

What training resources are available for learning EPPI-Reviewer?

EPPI-Reviewer provides documentation and training materials through its official channels. Your institution may also offer workshops or support for researchers using the software. The National Library of Medicine provides access to research methodology texts that complement software training by explaining systematic review principles.

Using the Evidence

Related Articles

• What Is Data Management? A Primer for Life Science Researchers
• Statistical Z-Table: How to Use It and Find Probabilities
• Master Data Management: A Practical Guide for Life Science Organizations
• Conducting Qualitative Interviews: A Guide for Life Science Researchers
• Choosing the Best Online Data Science Master's for Life Sciences Professionals

References and Further Reading

• Research Methods Resources. National Library of Medicine.
• EQUATOR Network. EQUATOR Network.
• Core Practices. Committee on Publication Ethics.
• NIH Grants and Funding. National Institutes of Health.
• ORCID for Researchers. ORCID.
• Data Management and Sharing Policy. National Institutes of Health.
• NCBI Literature Resources. National Center for Biotechnology Information.
• PubMed. National Library of Medicine.

This article is educational and does not replace institutional policy, professional advice, or applicable safety and regulatory requirements.