Evidence map›Paper›PMID 31592524›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2020

Leaf: an open-source, model-agnostic, data-driven web application for cohort discovery and translational biomedical research.

Nicholas J Dobbins, Clifford H Spital, Robert A Black, Jason M Morrison, Bas de Veer, Elizabeth Zampino, Robert D Harrington, Bethene D Britt, Kari A Stephens, Adam B Wilcox and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 10% 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

36 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

  1. Pooled it
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  10. Towards cross-application model-agnostic federated cohort discovery.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
  11. Article
  12. Article
  13. Article
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  15. LeafAI: query generator for clinical cohort discovery rivaling a human programmer.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  16. Article
  17. Article
  18. A Query Engine for Self-controlled Case Series, with an application to COVID-19 EHR data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    Article
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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

12 authors at 4 institutions in 1 country.

Nicholas J DobbinsDepartment of Biomedical Informatics and Medical Education, UW Medicine Research IT, University of Washington, Seattle, Washington, USA.
Clifford H SpitalUW Medicine Research IT, University of Washington, Seattle, Washington, USA.
Robert A BlackPopulation Health Analytics, University of Washington, Seattle, Washington, USA.
Jason M MorrisonClinical Research Informatics, St. Jude's Children's Research Hospital, Memphis, Tennessee, USA.
Bas de VeerUW Medicine Research IT, University of Washington, Seattle, Washington, USA.
Elizabeth ZampinoUW Medicine Research IT, University of Washington, Seattle, Washington, USA.
Robert D HarringtonDepartment of Medicine, Division of Infectious Disease, University of Washington, Seattle, Washington, USA.
Bethene D BrittUW Medicine Analytics, University of Washington, Seattle, Washington, USA.
Kari A StephensDepartment of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington, USA.
Adam B WilcoxDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.
Peter Tarczy-HornochDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.
Sean D MooneyDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.
University of Washington · USUniversity of Washington Medical Center · USInfectious Disease Research Institute · USSt. Jude Children's Research Hospital · US

Funding

Transform Dissemination and Implementation Science in CTSA ProgramsUL1TR002319 · NCATS · UNIVERSITY OF WASHINGTON · PI John K. Amory · 2017 to 2026
$100.0M
CD2H - The National COVID Cohort Collaborative (N3C) IDeA CTR CollaborationU24TR002306 · NCATS · UNIVERSITY OF COLORADO DENVER · PI CHUTE, CHRISTOPHER G, EICHMANN, DAVID A. · 2017 to 2021
$28.9M
NCATS NIH HHS U24 TR002306NCATS NIH HHS UL1 TR002319
6 · The paper itself

Abstract

objectiveAcademic medical centers and health systems are increasingly challenged with supporting appropriate secondary use of clinical data. Enterprise data warehouses have emerged as central resources for these data, but often require an informatician to extract meaningful information, limiting direct access by end users. To overcome this challenge, we have developed Leaf, a lightweight self-service web application for querying clinical data from heterogeneous data models and sources. MATERIALS AND

methodsLeaf utilizes a flexible biomedical concept system to define hierarchical concepts and ontologies. Each Leaf concept contains both textual representations and SQL query building blocks, exposed by a simple drag-and-drop user interface. Leaf generates abstract syntax trees which are compiled into dynamic SQL queries.

resultsLeaf is a successful production-supported tool at the University of Washington, which hosts a central Leaf instance querying an enterprise data warehouse with over 300 active users. Through the support of UW Medicine (https://uwmedicine.org), the Institute of Translational Health Sciences (https://www.iths.org), and the National Center for Data to Health (https://ctsa.ncats.nih.gov/cd2h/), Leaf source code has been released into the public domain at https://github.com/uwrit/leaf. DISCUSSION: Leaf allows the querying of single or multiple clinical databases simultaneously, even those of different data models. This enables fast installation without costly extraction or duplication.

conclusionsLeaf differs from existing cohort discovery tools because it does not specify a required data model and is designed to seamlessly leverage existing user authentication systems and clinical databases in situ. We believe Leaf to be useful for health system analytics, clinical research data warehouses, precision medicine biobanks, and clinical studies involving large patient cohorts.

Indexed as

Data WarehousingTranslational Research, BiomedicalUser-Computer InterfaceVocabulary, ControlledDatabases as TopicHumansInformation Storage and RetrievalInternetUnified Medical Language Systembiomedical informaticscloud computingcohort discoverydata integrationleafobservational health data sciences and informatics

Identifiers

PMID31592524
PMCPMC6913227
OpenAlexW2981864773

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.