Background: The reliable and usable (semi)automation of data
extraction can support the field of systematic review by reducing the
workload required to gather information about the conduct and
results of the included studies. This living systematic review examines
published approaches for data extraction from reports of clinical
studies.
Methods: We systematically and continually search MEDLINE,
Institute of Electrical and Electronics Engineers (IEEE), arXiv, and the
dblp computer science bibliography databases. Full text screening and
data extraction are conducted within an open-source living systematic
review application created for the purpose of this review. This
iteration of the living review includes publications up to a cut-off date
of 22 April 2020.
Results: In total, 53 publications are included in this version of our
review. Of these, 41 (77%) of the publications addressed extraction of
data from abstracts, while 14 (26%) used full texts. A total of 48 (90%)
publications developed and evaluated classifiers that used
randomised controlled trials as the main target texts. Over 30 entities
were extracted, with PICOs (population, intervention, comparator,
outcome) being the most frequently extracted. A description of their
datasets was provided by 49 publications (94%), but only seven (13%)
made the data publicly available. Code was made available by 10 (19%)
publications, and five (9%) implemented publicly available tools.
Conclusions: This living systematic review presents an overview of
(semi)automated data-extraction literature of interest to different
types of systematic review. We identified a broad evidence base of
publications describing data extraction for interventional reviews and
a small number of publications extracting epidemiological or diagnostic accuracy data. The lack of publicly available gold-standard
data for evaluation, and lack of application thereof, makes it difficult
to draw conclusions on which is the best-performing system for each
data extraction target. With this living review we aim to review the
literature continually
