Systematic reviewers used various approaches to data extraction and expressed several research needs: a survey.

Objective: Data extraction is a prerequisite for analyzing, summarizing, and interpreting evidence in systematic reviews. Yet guidance is limited, and little is known about current approaches. We surveyed systematic reviewers on their current approaches to data extraction, opinions on methods, and research needs.

Study Design And Setting: We developed a 29-question online survey and distributed it through relevant organizations, social media, and personal networks in 2022. Closed questions were evaluated using descriptive statistics, and open questions were analyzed using content analysis.

Results: 162 reviewers participated. Use of adapted (65%) or newly developed extraction forms (62%) was common. Generic forms were rarely used (14%). Spreadsheet software was the most popular extraction tool (83%). Piloting was reported by 74% of respondents and included a variety of approaches. Independent and duplicate extraction was considered the most appropriate approach to data collection (64%). About half of respondents agreed that blank forms and/or raw data should be published. Suggested research gaps were the effects of different methods on error rates (60%) and the use of data extraction support tools (46%).

Conclusion: Systematic reviewers used varying approaches to pilot data extraction. Methods to reduce errors and use of support tools such as (semi-)automation tools are top research gaps.