Evidence map›Paper›PMID 30901549›Full record

ReviewCell2019

Personalized Medicine and the Power of Electronic Health Records.

Noura S Abul-Husn, Eimear E Kenny

Abstract readReview
In one paragraph

Review in Cell, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 162 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
162citing papers in PubMed, 4 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.

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

162 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Genetically guided precision medicine clinical decision support tools: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2024
    Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
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  15. Recent Advances in AI and GenAI for Health Informatics.Healthcare (Basel, Switzerland) · 2026
    Review
  16. Review
  17. Benchmarking Foundation Models with Multimodal Public Electronic Health Records.IEEE journal of biomedical and health informatics · 2025
    Article
  18. Article
  19. Article
  20. Review

102 more citing papers are in PubMed but not listed here.

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

2 authors.

Noura S Abul-HusnThe Center for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Eimear E KennyThe Center for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Electronic address: eimear.kenny@mssm.edu.

Funding

MSHS Translational Science HubUL1TR001433 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI WRIGHT, ROSALIND J · 2015 to 2019
$26.6M
New Approaches for Empowering Studies of Asthma in Populations of African DescentR01HL104608 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI BARNES, KATHLEEN C, KENNY, EIMEAR ELIZABETH · 2011 to 2022
$23.1M
Incorporating genomics into the clinical care of diverse NYC childrenU01HG009610 · NHGRI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI GELB, BRUCE D, HOROWITZ, CAROL R · 2017 to 2021
$17.0M
Optimizing imputation for diverse populations in a distributed frameworkU01HG009080 · NHGRI · STANFORD UNIVERSITY · PI KENNY, EIMEAR ELIZABETH · 2016 to 2020
$5.2M
Study of coding variants in human obesity and their functional characterization using human iPSC-derived cellular modelsR01DK110113 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI LOOS, RUTH JF · 2016 to 2020
$2.8M
NCATS NIH HHS UL1 TR001433NHGRI NIH HHS U01 HG009080NHGRI NIH HHS U01 HG009610NHLBI NIH HHS R01 HL104608NIDDK NIH HHS R01 DK110113
6 · The paper itself

Abstract

Personalized medicine has largely been enabled by the integration of genomic and other data with electronic health records (EHRs) in the United States and elsewhere. Increased EHR adoption across various clinical settings and the establishment of EHR-linked population-based biobanks provide unprecedented opportunities for the types of translational and implementation research that drive personalized medicine. We review advances in the digitization of health information and the proliferation of genomic research in health systems and provide insights into emerging paths for the widespread implementation of personalized medicine.

Indexed as

Electronic Health RecordsGenetic TestingGenome, HumanGenomicsHumansPrecision MedicineUnited States

Identifiers

PMID30901549
PMCPMC6921466

What OpenQuestion holds

Textmetadata
LicenceTDM
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.