Evidence map›Paper›PMID 26911808›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2016

Harnessing next-generation informatics for personalizing medicine: a report from AMIA's 2014 Health Policy Invitational Meeting.

Laura K Wiley, Peter Tarczy-Hornoch, Joshua C Denny, Robert R Freimuth, Casey L Overby, Nigam Shah, Ross D Martin, Indra Neil Sarkar

Abstract readConference Proceedings
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Clinical Research Informatics: a Decade-in-Review.Yearbook of medical informatics · 2024
    Review
  2. Opportunities and obstacles for deep learning in biology and medicine.Journal of the Royal Society, Interface · 2018
    Review
  3. Article
  4. 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

8 authors.

Laura K WileyDepartment of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.
Peter Tarczy-HornochDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.
Joshua C DennyDepartment of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.
Robert R FreimuthDepartment of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
Casey L OverbyProgram for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Nigam ShahCenter for Biomedical Informatics Research, Stanford University, Stanford, California, USA.
Ross D MartinChesapeake Regional Information System for our Patients (CRISP), Columbia, Maryland, USA ross.martin@crisphealth.org.
Indra Neil SarkarCenter for Biomedical Informatics, Brown University, Providence, Rhode Island, USA.

Funding

Training Program on Genetic Variation and Human PhenotypesT32GM080178 · NIGMS · VANDERBILT UNIVERSITY · PI COX, NANCY J, SAMUELS, DAVID C · 2007 to 2021
$3.1M
AMIA Health Policy Conference SeriesR13HS021825 · AHRQ · AMERICAN MEDICAL INFORMATICS ASSN · PI KUPERMAN, GILAD · 2012 to 2014
$230k
AHRQ HHS 1R13HS021825-01AHRQ HHS R13 HS021825
6 · The paper itself

Abstract

The American Medical Informatics Association convened the 2014 Health Policy Invitational Meeting to develop recommendations for updates to current policies and to establish an informatics research agenda for personalizing medicine. In particular, the meeting focused on discussing informatics challenges related to personalizing care through the integration of genomic or other high-volume biomolecular data with data from clinical systems to make health care more efficient and effective. This report summarizes the findings (n = 6) and recommendations (n = 15) from the policy meeting, which were clustered into 3 broad areas: (1) policies governing data access for research and personalization of care; (2) policy and research needs for evolving data interpretation and knowledge representation; and (3) policy and research needs to ensure data integrity and preservation. The meeting outcome underscored the need to address a number of important policy and technical considerations in order to realize the potential of personalized or precision medicine in actual clinical contexts.

Indexed as

Health PolicyMedical InformaticsPrecision MedicineHumansSocieties, MedicalUnited Stateshealth policylearning health care systemmedical informaticsprecision medicinetranslational bioinformatics

Identifiers

PMID26911808
PMCPMC6457095

What OpenQuestion holds

Textmetadata
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.