Evidence map›Paper›PMID 35499859›Full record

ArticleJMIR medical informatics2022

Web-Based Software Tools for Systematic Literature Review in Medicine: Systematic Search and Feature Analysis.

Kathryn Cowie, Asad Rahmatullah, Nicole Hardy, Karl Holub, Kevin Kallmes

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 25 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 5 pooled it
11.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 5 syntheses or guidelines pooled it, 68 citations in OpenAlex.

  1. Pooled it
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  4. Pooled it
  5. Pooled it
  6. Review
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  11. Evaluating AI Performance in Systematic Literature Reviews for HEOR: A Case Study.Journal of health economics and outcomes research · 2026
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  12. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Kathryn CowieNested Knowledge, Saint Paul, MN, United States.ORCID 0000-0002-4216-851X
Asad RahmatullahNested Knowledge, Saint Paul, MN, United States.ORCID 0000-0003-3251-8114
Nicole HardyNested Knowledge, Saint Paul, MN, United States.ORCID 0000-0002-1597-0371
Karl HolubNested Knowledge, Saint Paul, MN, United States.ORCID 0000-0002-2010-2712
Kevin KallmesNested Knowledge, Saint Paul, MN, United States.ORCID 0000-0001-5439-4074

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSystematic reviews (SRs) are central to evaluating therapies but have high costs in terms of both time and money. Many software tools exist to assist with SRs, but most tools do not support the full process, and transparency and replicability of SR depend on performing and presenting evidence according to established best practices.

objectiveThis study aims to provide a basis for comparing and selecting between web-based software tools that support SR, by conducting a feature-by-feature comparison of SR tools.

methodsWe searched for SR tools by reviewing any such tool listed in the SR Toolbox, previous reviews of SR tools, and qualitative Google searching. We included all SR tools that were currently functional and required no coding, and excluded reference managers, desktop applications, and statistical software. The list of features to assess was populated by combining all features assessed in 4 previous reviews of SR tools; we also added 5 features (manual addition, screening automation, dual extraction, living review, and public outputs) that were independently noted as best practices or enhancements of transparency and replicability. Then, 2 reviewers assigned binary present or absent assessments to all SR tools with respect to all features, and a third reviewer adjudicated all disagreements.

resultsOf the 53 SR tools found, 55% (29/53) were excluded, leaving 45% (24/53) for assessment. In total, 30 features were assessed across 6 classes, and the interobserver agreement was 86.46%. Giotto Compliance (27/30, 90%), DistillerSR (26/30, 87%), and Nested Knowledge (26/30, 87%) support the most features, followed by EPPI-Reviewer Web (25/30, 83%), LitStream (23/30, 77%), JBI SUMARI (21/30, 70%), and SRDB.PRO (VTS Software) (21/30, 70%). Fewer than half of all the features assessed are supported by 7 tools: RobotAnalyst (National Centre for Text Mining), SRDR (Agency for Healthcare Research and Quality), SyRF (Systematic Review Facility), Data Abstraction Assistant (Center for Evidence Synthesis in Health), SR Accelerator (Institute for Evidence-Based Healthcare), RobotReviewer (RobotReviewer), and COVID-NMA (COVID-NMA). Notably, of the 24 tools, only 10 (42%) support direct search, only 7 (29%) offer dual extraction, and only 13 (54%) offer living/updatable reviews.

conclusionsDistillerSR, Nested Knowledge, and EPPI-Reviewer Web each offer a high density of SR-focused web-based tools. By transparent comparison and discussion regarding SR tool functionality, the medical community can both choose among existing software offerings and note the areas of growth needed, most notably in the support of living reviews.

Indexed as

feature analysissoftware toolssystematic reviews

Identifiers

PMID35499859
PMCPMC9112080
OpenAlexW4225297356

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.