Literature DB >> 31302205

A randomized trial provided new evidence on the accuracy and efficiency of traditional vs. electronically annotated abstraction approaches in systematic reviews.

Tianjing Li1, Ian J Saldanha2, Jens Jap3, Bryant T Smith3, Joseph Canner4, Susan M Hutfless5, Vernal Branch6, Simona Carini7, Wiley Chan8, Berry de Bruijn9, Byron C Wallace10, Sandra A Walsh11, Elizabeth J Whamond12, M Hassan Murad13, Ida Sim14, Jesse A Berlin15, Joseph Lau3, Kay Dickersin16, Christopher H Schmid17.   

Abstract

OBJECTIVES: Data Abstraction Assistant (DAA) is a software for linking items abstracted into a data collection form for a systematic review to their locations in a study report. We conducted a randomized cross-over trial that compared DAA-facilitated single-data abstraction plus verification ("DAA verification"), single data abstraction plus verification ("regular verification"), and independent dual data abstraction plus adjudication ("independent abstraction"). STUDY DESIGN AND
SETTING: This study is an online randomized cross-over trial with 26 pairs of data abstractors. Each pair abstracted data from six articles, two per approach. Outcomes were the proportion of errors and time taken.
RESULTS: Overall proportion of errors was 17% for DAA verification, 16% for regular verification, and 15% for independent abstraction. DAA verification was associated with higher odds of errors when compared with regular verification (adjusted odds ratio [OR] = 1.08; 95% confidence interval [CI]: 0.99-1.17) or independent abstraction (adjusted OR = 1.12; 95% CI: 1.03-1.22). For each article, DAA verification took 20 minutes (95% CI: 1-40) longer than regular verification, but 46 minutes (95% CI: 26 to 66) shorter than independent abstraction.
CONCLUSION: Independent abstraction may only be necessary for complex data items. DAA provides an audit trail that is crucial for reproducible research.
Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Accuracy; Data abstraction; Efficiency; Randomized cross-over trial; Software application; Systematic review

Mesh:

Year:  2019        PMID: 31302205     DOI: 10.1016/j.jclinepi.2019.07.005

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  3 in total

1.  Effectiveness of interventions for dry eye: a protocol for an overview of systematic reviews.

Authors:  Paul McCann; Zanna Kruoch; Riaz Qureshi; Tianjing Li
Journal:  BMJ Open       Date:  2022-06-07       Impact factor: 3.006

Review 2.  What Do We Really Know about the Effectiveness of Glaucoma Interventions?: An Overview of Systematic Reviews.

Authors:  Riaz Qureshi; Augusto Azuara-Blanco; Manuele Michelessi; Gianni Virgili; João Barbosa Breda; Carlo Alberto Cutolo; Marta Pazos; Andreas Katsanos; Gerhard Garhöfer; Miriam Kolko; Verena Prokosch-Willing; Ali Ahmed Al Rajhi; Flora Lum; David Musch; Steven Gedde; Tianjing Li
Journal:  Ophthalmol Glaucoma       Date:  2021-02-09

3.  The Systematic Review Data Repository (SRDR): descriptive characteristics of publicly available data and opportunities for research.

Authors:  Ian J Saldanha; Bryant T Smith; Evangelia Ntzani; Jens Jap; Ethan M Balk; Joseph Lau
Journal:  Syst Rev       Date:  2019-12-20
  3 in total

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