Evidence map›Paper›PMID 37583654›Full record

ArticleJAMIA open2023

Integrating row level security in i2b2: segregation of medical records into data marts without data replication and synchronization.

Raphael Scheible, Fabian Thomczyk, Marco Blum, Micha Rautenberg, Andrea Prunotto, Suhail Yazijy, Martin Boeker

Abstract read
In one paragraph

Article in JAMIA open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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.

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

3 citing papers in PubMed.

  1. 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

7 authors.

Raphael ScheibleInstitute of Artificial Intelligence and Informatics in Medicine (AIIM), Chair of Medical Informatics, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.ORCID https://orcid.org/0000-0003-2067-5569
Fabian ThomczykData Inintegration Center (DIC), University of Freiburg, Freiburg, Germany.
Marco BlumData Inintegration Center (DIC), University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0003-0664-343X
Micha RautenbergInstitute of Medical Biometry and Statistics, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0001-6666-7666
Andrea PrunottoData Inintegration Center (DIC), University of Freiburg, Freiburg, Germany.
Suhail YazijyInstitute of Medical Biometry and Statistics, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Martin BoekerInstitute of Artificial Intelligence and Informatics in Medicine (AIIM), Chair of Medical Informatics, University Hospital rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.ORCID https://orcid.org/0000-0003-2972-2042

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: i2b2 offers the possibility to store biomedical data of different projects in subject oriented data marts of the data warehouse, which potentially requires data replication between different projects and also data synchronization in case of data changes. We present an approach that can save this effort and assess its query performance in a case study that reflects real-world scenarios. Material and Methods: For data segregation, we used PostgreSQL's row level security (RLS) feature, the unit test framework pgTAP for validation and testing as well as the i2b2 application. No change of the i2b2 code was required. Instead, to leverage orchestration and deployment, we additionally implemented a command line interface (CLI). We evaluated performance using 3 different queries generated by i2b2, which we performed on an enlarged Harvard demo dataset. Results: We introduce the open source Python CLI i2b2rls, which orchestrates and manages security roles to implement data marts so that they do not need to be replicated and synchronized as different i2b2 projects. Our evaluation showed that our approach is on average 3.55 and on median 2.71 times slower compared to classic i2b2 data marts, but has more flexibility and easier setup. Conclusion: The RLS-based approach is particularly useful in a scenario with many projects, where data is constantly updated, user and group requirements change frequently or complex user authorization requirements have to be defined. The approach applies to both the i2b2 interface and direct database access.

Indexed as

databasesdata securitydata segregationdata-warehousingi2b2software

Identifiers

PMID37583654
PMCPMC10425194

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.