Evidence map›Paper›PMID 19309514›Full record

ArticleBMC medical informatics and decision making2009

A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine.

Kensaku Kawamoto, David F Lobach, Huntington F Willard, Geoffrey S Ginsburg

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 2 pooled it
5.8field-weighted citation impact, top 3% of its field
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

44 citing papers in PubMed, 2 syntheses or guidelines pooled it, 113 citations in OpenAlex.

  1. Genetically guided precision medicine clinical decision support tools: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2024
    Pooled it
  2. Clinical decision support for genetically guided personalized medicine: a systematic review.Journal of the American Medical Informatics Association : JAMIA
    Pooled it
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Of Screening, Stratification, and Scores.Journal of personalized medicine · 2021
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Clinical decision support alert malfunctions: analysis and empirically derived taxonomy.Journal of the American Medical Informatics Association : JAMIA · 2018
    Article
  13. Design Recommendations for Pharmacogenomics Clinical Decision Support Systems.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2017
    Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Genetics and primary care: where are we headed?Journal of translational medicine · 2014
    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

4 authors at 3 institutions in 1 country.

Kensaku KawamotoDivision of Clinical Informatics, Department of Community and Family Medicine, Box 104007, Duke University Medical Center, Durham, North Carolina 27710, USA. kawam001@mc.duke.edu
David F Lobach
Huntington F Willard
Geoffrey S Ginsburg
Duke University · USDuke Medical Center · USDuke University Hospital · US

Funding

Enabling Personalized Medicine through Clincal Decision SupportK01HG004645 · NHGRI · DUKE UNIVERSITY · PI KAWAMOTO, KENSAKU · 2008 to 2010
$559k
NHGRI NIH HHS K01HG004645
6 · The paper itself

Abstract

backgroundIn recent years, the completion of the Human Genome Project and other rapid advances in genomics have led to increasing anticipation of an era of genomic and personalized medicine, in which an individual's health is optimized through the use of all available patient data, including data on the individual's genome and its downstream products. Genomic and personalized medicine could transform healthcare systems and catalyze significant reductions in morbidity, mortality, and overall healthcare costs. DISCUSSION: Critical to the achievement of more efficient and effective healthcare enabled by genomics is the establishment of a robust, nationwide clinical decision support infrastructure that assists clinicians in their use of genomic assays to guide disease prevention, diagnosis, and therapy. Requisite components of this infrastructure include the standardized representation of genomic and non-genomic patient data across health information systems; centrally managed repositories of computer-processable medical knowledge; and standardized approaches for applying these knowledge resources against patient data to generate and deliver patient-specific care recommendations. Here, we provide recommendations for establishing a national decision support infrastructure for genomic and personalized medicine that fulfills these needs, leverages existing resources, and is aligned with the Roadmap for National Action on Clinical Decision Support commissioned by the U.S. Office of the National Coordinator for Health Information Technology. Critical to the establishment of this infrastructure will be strong leadership and substantial funding from the federal government. SUMMARY: A national clinical decision support infrastructure will be required for reaping the full benefits of genomic and personalized medicine. Essential components of this infrastructure include standards for data representation; centrally managed knowledge repositories; and standardized approaches for leveraging these knowledge repositories to generate patient-specific care recommendations at the point of care.

Indexed as

GenomicsPersonal Health ServicesDatabases as TopicDecision Making, Computer-AssistedDecision Support Systems, ClinicalGenome, HumanHumansInformation SystemsUnited States

Identifiers

PMID19309514
PMCPMC2666673
OpenAlexW2158631567

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.