Data Extraction Methods
in Systematic Reviews
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There are different types of data extraction methods and each one takes more or less time to generate a standardized data extraction form. This article will show you these data extraction methods.
1. Systematic Review Software
Systematic review software is used to streamline parts of the systematic review process, such as data extraction and screening. The data extraction functionality of these tools can save you time and effort as a reviewer.
Some systematic review software allows you to create and publish a data extraction template that has features such as text fields, sections, and subsection headings. These systematic review softwares also enable you to perform dual and single reviewer data extraction. You can also review the extractions for a consensus in case of any discrepancies.
These softwares can also allow you to export the extracted data and quality assessment to a CSV for further processing and analysis.
2. Spreadsheet or Database Software
You can also use spreadsheet or database software to generate data extraction forms during a systematic review process. Spreadsheet software like Microsoft Excel has features such as a drop-down menu and range checks that hasten the process of data extraction.
Data extraction from unstructured documents for living reviews can also be undertaken using database software like Microsoft Access. Such relational databases usually enable you to collect information in categories like intervention, outcomes, and author details.
3. Survey or Form Software
Survey and form software can create data extraction forms with many questions, including multiple-choice and drop-down. You can then put information collected from these forms into spreadsheets or database software where you can analyze the data.
4. Optical Character Recognition Software
Optical character recognition software is used to extract data from physical documents like newspapers and journals. During the literary research step in the systematic review process, you may bump into a physical document containing data relevant to your research question.
Instead of typing the information word by word during data extraction, you may work faster by using optical character recognition software—technology that converts physical data into a digital version.
5. Google Docs and Other Electronic Documents
Data extraction forms for cross-sectional studies can also be created using electronic documents such as Google Docs and Microsoft Word. However, this method takes longer to complete and is prone to more errors in data entry.
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What Should You Extract From the Individual Studies?
The research question of the systematic review should guide you on what data to extract from individual studies. For example, you may use the PICO framework to gather useful data.
In case of an intervention question, your data extraction form should collect data such as :
- Information about the article
- Information about the study
- Patient demographics
- Intervention
- Outcomes
In Conclusion
Data extraction enables reviewers to collect data that will be useful during the data analysis stage of the systematic review process. There are different data extraction methods, such as systematic review software, spreadsheets, and Google docs. You can also extract data from physical sources using optical character recognition software. There are benefits and limitations to each data extraction method, so consider factors such as the data entry process (user friendliness), the cost of software, and shareability.
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