1. Systematic Review Assistant De-duplication Module (SRA-DM)
Elaine Beller
on behalf of
Matt Carter, John Rathbone, Paul Glasziou
Centre for Research in Evidence-Based Practice
Bond University, Australia

2. The problem The solution
search multiple databases for trials
for specific reviews
maintain trials citation registers (e.g. CRS)
same citation in multiple databases
journal overlap MEDLINE and EMBASE 10% to 75%
citation management software - very simple duplicate detection
manual detection of duplicates needed
or, reviewers screening same citation more than once!
de-duplication tool within Systematic Review Assistant package (SRA-DM)
Aims
reduce time taken to produce systematic reviews
reduce time spent maintaining trials citation registers

3. Methods Heuristic based approach
Iterative development of algorithm (4 iterations)
Benchmark dataset of n=1988 citations
Validation datasets
cytology screening tests (n=1856)
stroke (n=1292)
haematology (n=1415)
Sensitivity, specificity against manual de-duplication

4. PICO P – search results from typical systematic reviews
I – Index test - SRA-DM
C – Comparator test – EndNote
O – human being de-duplication
Outcome measures - sensitivity & specificity

5. Sensitivity and Specificity
correct classification of a record as unique
important for systematic reviews
don’t want to miss any included studies
false positive detection of duplicates bad!
particularly if process fully automated
Sensitivity
correct classification of a record as duplicate
higher sensitivity reduces manual detection or subsequent duplicate screening by reviewers

6. Results - What caused duplicates?
Variations in author name
First name / last name sequence
Initials / full name
Missing author names
Abbreviated / full journal names
Text accents (e.g. French/German/Spanish)
‘The’ used / not used in journal and article titles
Recording of page numbers (e.g vs 590-5)

7. Results – SRA-DM vs Endnote
Sensitivity
Specificity 2 1 2 4
139 81 38
125
134
391
518 87
Numbers on bars indicate # incorrectly identified as duplicates
Numbers over bars indicate # missed duplicates

20. Where does SRA-DM fit? Now
aids manual de-duplication of citations from multiple databases
present user with de-duplicated set for screening
Future
integration of algorithm in other tools that automatically search and snowball from citations
present automated screener software with de-duplicated set

21. Summary De-duplication tool for merged libraries of citations
Good sensitivity, high specificity
finds most duplicates
algorithm optimised for very low false positives
Common library and software formats supported
XML
RIS
CSV
Open source, free to use
Algorithm can be embedded in other tools