Evidence map›Paper›PMID 30085008›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2018

Web services for data warehouses: OMOP and PCORnet on i2b2.

Jeffrey G Klann, Lori C Phillips, Christopher Herrick, Matthew A H Joss, Kavishwar B Wagholikar, Shawn N Murphy

Registry-linked trialAbstract 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. It is linked to trial NCT03911687 (Communicating Narrative Concerns Entered by RNs), which is not on this map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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.

NCT03911687 nacompletednot on this mapstarted 2020, after this paper: background citation

Communicating Narrative Concerns Entered by RNs (CONCERN) Clinical Decision Support (CDS) System

TypeinterventionalSponsorColumbia UniversityRan2020 to 2022Enrolled60,893ConditionsHospital Acquired ConditionArmsCONCERN CDS system notification
3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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  6. Article
  7. Review
  8. Clinical Data Warehousing: A Scoping Review.Journal of the Society for Clinical Data Management · 2024
    Article
  9. Article
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  12. Article
  13. Article
  14. Article
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  18. Article
  19. Deep-learning-based automated terminology mapping in OMOP-CDM.Journal of the American Medical Informatics Association : JAMIA · 2021
    Article
  20. 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

6 authors.

Jeffrey G KlannResearch Information Science and Computing, Partners Healthcare, Boston, Massachusetts, USA.
Lori C PhillipsResearch Information Science and Computing, Partners Healthcare, Boston, Massachusetts, USA.
Christopher HerrickResearch Information Science and Computing, Partners Healthcare, Boston, Massachusetts, USA.
Matthew A H JossResearch Information Science and Computing, Partners Healthcare, Boston, Massachusetts, USA.
Kavishwar B WagholikarResearch Information Science and Computing, Partners Healthcare, Boston, Massachusetts, USA.
Shawn N MurphyResearch Information Science and Computing, Partners Healthcare, Boston, Massachusetts, USA.

Funding

TrainingU54HG007963 · NHGRI · HARVARD MEDICAL SCHOOL · PI KOHANE, ISAAC S., MURPHY, SHAWN N · 2014 to 2018
$18.3M
Developing i2b2 into a Health Innovation Platform for Clinical Decision Support in the Genomics EraR01HG009174 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI ARONSON, SAMUEL JEFFREY, MACRAE, CALUM A. · 2016 to 2019
$2.9M
A Framework to Enhance Decision Support by Invoking NLP: Methods and ApplicationsR00LM011575 · NLM · MASSACHUSETTS GENERAL HOSPITAL · PI WAGHOLIKAR, KAVISHWAR B. · 2016 to 2018
$749k
NHGRI NIH HHS R01 HG009174NHGRI NIH HHS U54 HG007963NLM NIH HHS R00 LM011575
6 · The paper itself

Abstract

Objective: Healthcare organizations use research data models supported by projects and tools that interest them, which often means organizations must support the same data in multiple models. The healthcare research ecosystem would benefit if tools and projects could be adopted independently from the underlying data model. Here, we introduce the concept of a reusable application programming interface (API) for healthcare and show that the i2b2 API can be adapted to support diverse patient-centric data models. Materials and Methods: We develop methodology for extending i2b2's pre-existing API to query additional data models, using i2b2's recent "multi-fact-table querying" feature. Our method involves developing data-model-specific i2b2 ontologies and mapping these to query non-standard table structure. Results: We implement this methodology to query OMOP and PCORnet models, which we validate with the i2b2 query tool. We implement the entire PCORnet data model and a five-domain subset of the OMOP model. We also demonstrate that additional, ancillary data model columns can be modeled and queried as i2b2 "modifiers." Discussion: i2b2's REST API can be used to query multiple healthcare data models, enabling shared tooling to have a choice of backend data stores. This enables separation between data model and software tooling for some of the more popular open analytic data models in healthcare. Conclusion: This methodology immediately allows querying OMOP and PCORnet using the i2b2 API. It is released as an open-source set of Docker images, and also on the i2b2 community wiki.

Indexed as

Big DataElectronic Health RecordsInternetBiomedical ResearchDatabases, FactualData WarehousingHumansModels, TheoreticalSoftwareVocabulary, Controlled

Identifiers

PMID30085008
PMCPMC6188504

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

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.