Evidence map›Paper›PMID 39156149›Full record

ArticleKidney international reports2024

Bridging the Gap in Genomic Implementation: Identifying User Needs for Precision Nephrology.

Jerard Z Kneifati-Hayek, Teena Zachariah, Wooin Ahn, Atlas Khan, Krzysztof Kiryluk, Sumit Mohan, Chunhua Weng, Ali G Gharavi, Jordan G Nestor

Abstract read
In one paragraph

Article in Kidney international reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

9 authors.

Jerard Z Kneifati-HayekDivision of General Medicine, Department of Medicine, Columbia University, New York, USA.
Teena ZachariahDivision of Nephrology, Department of Medicine, Columbia University, New York, USA.
Wooin AhnDivision of Nephrology, Department of Medicine, Columbia University, New York, USA.
Atlas KhanDivision of Nephrology, Department of Medicine, Columbia University, New York, USA.
Krzysztof KirylukDivision of Nephrology, Department of Medicine, Columbia University, New York, USA.
Sumit MohanDivision of Nephrology, Department of Medicine, Columbia University, New York, USA.
Chunhua WengDepartment of Biomedical Informatics, Columbia University, New York, USA.
Ali G GharaviDivision of Nephrology, Department of Medicine, Columbia University, New York, USA.
Jordan G NestorDivision of Nephrology, Department of Medicine, Columbia University, New York, USA.

Funding

Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
Institutional Career Development CoreKL2TR001874 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GENKINGER, JEANINE M., SHIMBO, DAICHI · 2016 to 2025
$13.6M
NCATS NIH HHS KL2 TR001874NCATS NIH HHS UL1 TR001873
6 · The paper itself

Abstract

Introduction: Genomic medicine holds transformative potential for personalized nephrology care; however, its clinical integration poses challenges. Automated clinical decision support (CDS) systems in the electronic health record (EHR) offer a promising solution but have shown limited impact. This study aims to glean practical insights into nephrologists' challenges using genomic resources, informing precision nephrology decision support tools. Methods: We conducted an anonymous electronic survey among US nephrologists from January 19, 2021 to May 19, 2021, guided by the Consolidated Framework for Implementation Research. It assessed practice characteristics, genomic resource utilization, attitudes, perceived knowledge, self-efficacy, and factors influencing genetic testing decisions. Survey links were primarily shared with National Kidney Foundation members. Results: We analyzed 319 surveys, with most respondents specializing in adult nephrology. Although respondents generally acknowledged the clinical use of genomic resources, varying levels of perceived knowledge and self-efficacy were evident regarding precision nephrology workflows. Barriers to genetic testing included cost/insurance coverage and limited genomics experience. Conclusion: The study illuminates specific hurdles nephrologists face using genomic resources. The findings are a valuable contribution to genomic implementation research, highlighting the significance of developing tailored interventions to support clinicians in using genomic resources effectively. These findings can guide the future development of CDS systems in the EHR. Addressing unmet informational and workflow support needs can enhance the integration of genomics into clinical practice, advancing personalized nephrology care and improving kidney disease outcomes. Further research should focus on interventions promoting seamless precision nephrology care integration.

Indexed as

clinical decision supportelectronic health recordgenetic kidney diseasegenomics implementationprecision medicine

Identifiers

PMID39156149
PMCPMC11328575

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.