Data extraction methods: an analysis of internal reporting discrepancies in single manuscripts and practical advice

Ref ID 371
First Author L. Puljak
Journal JOURNAL OF CLINICAL EPIDEMIOLOGY
Year Of Publishing 2020
URL https://www.sciencedirect.com/science/article/pii/S0895435619302227
Keywords • Error
• Single reviewer
• Abstract / summary
• General medical
Problem(s) • Data extraction errors and double counting
• Single reviewer / lack of double checking
Article Type Editorial
Article Subtype Discussion piece
First Author Country Croatia
Aim To discuss examples of internal reporting discrepancies that can be found in a single source and examples from some published systematic reviews.
Level of Investigation Descriptive
Summary of Findings The authors highlight possible types of internal reporting discrepancies which include: Abstract-text discrepancies (Discrepancies between the abstract and the full-text of a manuscript); Within-the-full-text discrepancies (Discrepancies in different parts of the body of a manuscript); Text-figure discrepancies (Discrepancies between a figure and the full-text of a manuscript); Text-table discrepancies (Discrepancies between a table and the full text of a manuscript); Multiple discrepancies (Discrepancies in multiple sections of the same manuscript). The authors provide a series of recommendations to help mitigate discrepancies including use of two systematic review authors conducting data extraction independently.
Number of systematic reviews included 2
Number of eligible systematic reviews assessed 6
Treatment impacted No
Treatment impacted description
Interpretation impacted Not Applicable
Interpretation impacted description