Evaluating Data Abstraction Assistant, a novel software application for data abstraction during systematic reviews: protocol for a randomized controlled trial

摘要

Background Data ion, a critical systematic review step, is time-consuming and prone to errors. Current standards for approaches to data ion rest on a weak evidence base. We developed the Data ion Assistant (DAA), a novel software application designed to facilitate the ion process by allowing users to (1) view study article PDFs juxtaposed to electronic data ion forms linked to a data ion system, (2) highlight (or “pin”) the location of the text in the PDF, and (3) copy relevant text from the PDF into the form. We describe the design of a randomized controlled trial (RCT) that compares the relative effectiveness of (A) DAA-facilitated single ion plus verification by a second person, (B) traditional (non-DAA-facilitated) single ion plus verification by a second person, and (C) traditional independent dual ion plus adjudication to ascertain the accuracy and efficiency of ion. Methods This is an online, randomized, three-arm, crossover trial. We will enroll 24 pairs of ors (i.e., sample size is 48 participants), each pair comprising one less and one more experienced or. Pairs will be randomized to data from six articles, two under each of the three approaches. ors will complete pre-tested data ion forms using the Systematic Review Data Repository (SRDR), an online data ion system. The primary outcomes are (1) proportion of data items ed that constitute an error (compared with an answer key) and (2) total time taken to complete ion (by two ors in the pair, including verification and/or adjudication). Discussion The DAA trial uses a practical design to test a novel software application as a tool to help improve the accuracy and efficiency of the data ion process during systematic reviews. Findings from the DAA trial will provide much-needed evidence to strengthen current recommendations for data ion approaches. Trial registration The trial is registered at National Information Center on Health Services Research and Health Care Technology (NICHSR) under Registration # HSRP20152269: https://wwwcf.nlm.nih.gov/hsr_project/view_hsrproj_record.cfm?NLMUNIQUE_ID=20152269&SEARCH_FOR=Tianjing%20Li . All items from the World Health Organization Trial Registration Data Set are covered at various locations in this protocol. Protocol version and date: This is version 2.0 of the protocol, dated September 6, 2016. As needed, we will communicate any protocol amendments to the Institutional Review Boards (IRBs) of Johns Hopkins Bloomberg School of Public Health (JHBSPH) and Brown University. We also will make appropriate as-needed modifications to the NICHSR website in a timely fashion.