Objectives: To introduce steps for achieving efficient, high-quality data abstraction. Workshop participants will gain hands-on experience and an understanding of how the data abstraction process for systematic reviews can be optimized by carefully thinking about which data to collect, selecting data collection tools such as the Cochrane Author Support Tool (CAST) and Systematic Review Data Repository (SRDR), constructing data collection forms, abstracting and managing data.
Description: Data abstraction for systematic reviews is essential to ensure accurate analyses and appropriate conclusions and inferences. This workshop will walk participants through steps for high-quality data abstraction as highlighted by Li (Annals 2015): namely:
1. develop outlines and identify data elements;
2. assemble and group data elements;
3. Frame data abstraction items;
4. develop forms;
5. pilot test forms;
6. train data abstractors;
7. implement quality assurance plan;
8. export and clean data for analysis.
We will demonstrate these steps with a hands-on exercise using SRDR (Ip 2012; http://srdr.ahrq.gov) and sample data as a case example. A discussion session at the end of the exercise will be held to summarize the take-home messages and welcome any questions and comments. We will encourage participants to share their perspectives and experiences of data abstraction, with the goal of continuing to improve this important step in conducting systematic reviews.