Evidence map›Paper›PMID 29092054›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2018

Characteristics of knowledge content in a curated online evidence library.

Sowmya Varada, Ronilda Lacson, Ali S Raja, Ivan K Ip, Louise Schneider, David Osterbur, Paul Bain, Nicole Vetrano, Jacqueline Cellini, Carol Mita and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 13% 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

7 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Machine Learning Model Drift: Predicting Diagnostic Imaging Follow-Up as a Case Example.Journal of the American College of Radiology : JACR · 2022
    Article
  4. Article
  5. Can emergency department provider notes help to achieve more dynamic clinical decision support?Journal of the American College of Emergency Physicians open · 2020
    Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 5 institutions in 1 country.

Sowmya VaradaCenter for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
Ronilda LacsonCenter for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
Ali S RajaCenter for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
Ivan K IpCenter for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
Louise SchneiderCenter for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
David OsterburHarvard Medical School, Boston, MA, USA.
Paul BainHarvard Medical School, Boston, MA, USA.
Nicole VetranoCenter for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
Jacqueline CelliniHarvard Medical School, Boston, MA, USA.
Carol MitaHarvard Medical School, Boston, MA, USA.
Margaret ColettiAgoos Medical Library/Knowledge Services, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Julia WhelanAgoos Medical Library/Knowledge Services, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Ramin KhorasaniCenter for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
Brigham and Women's Hospital · USHarvard University · USBeth Israel Deaconess Medical Center · USMassachusetts General Hospital · USBoston Public Library · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To describe types of recommendations represented in a curated online evidence library, report on the quality of evidence-based recommendations pertaining to diagnostic imaging exams, and assess underlying knowledge representation. Materials and Methods: The evidence library is populated with clinical decision rules, professional society guidelines, and locally developed best practice guidelines. Individual recommendations were graded based on a standard methodology and compared using chi-square test. Strength of evidence ranged from grade 1 (systematic review) through grade 5 (recommendations based on expert opinion). Finally, variations in the underlying representation of these recommendations were identified. Results: The library contains 546 individual imaging-related recommendations. Only 15% (16/106) of recommendations from clinical decision rules were grade 5 vs 83% (526/636) from professional society practice guidelines and local best practice guidelines that cited grade 5 studies (P < .0001). Minor head trauma, pulmonary embolism, and appendicitis were topic areas supported by the highest quality of evidence. Three main variations in underlying representations of recommendations were "single-decision," "branching," and "score-based." Discussion: Most recommendations were grade 5, largely because studies to test and validate many recommendations were absent. Recommendation types vary in amount and complexity and, accordingly, the structure and syntax of statements they generate. However, they can be represented in single-decision, branching, and score-based representations. Conclusion: In a curated evidence library with graded imaging-based recommendations, evidence quality varied widely, with decision rules providing the highest-quality recommendations. The library may be helpful in highlighting evidence gaps, comparing recommendations from varied sources on similar clinical topics, and prioritizing imaging recommendations to inform clinical decision support implementation.

Indexed as

Decision Support Systems, ClinicalEvidence-Based PracticeKnowledge BasesDiagnostic ImagingHumansPractice Guidelines as Topic

Identifiers

PMID29092054
PMCPMC7646968
OpenAlexW2765093928

What OpenQuestion holds

Textmetadata
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.