Evidence map›Paper›PMID 32100012›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2020

Language matters: precision health as a cross-cutting care, research and policy agenda.

Philip R O Payne, Don E Detmer

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2020. 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
  2. Article
  3. 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

2 authors.

Philip R O PayneInstitute for Informatics, Washington University School of Medicine, St. Louis, Missouri, USA.
Don E DetmerDepartment of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The biomedical research and healthcare delivery communities have increasingly come to focus their attention on the role of data and computation in order to improve the quality, safety, costs, and outcomes of both wellness promotion and care delivery. Depending on the scale of such efforts, and the environments in which they are situated, they are referred to variably as personalized or precision medicine, population health, clinical transformation, value-driven care, or value-based transformation. Despite the original intent of many efforts and publications that have sought to define personalized, precision, or data-driven approaches to improving health and wellness, the use of such terminology in current practice often treats said activities as discrete areas of endeavor within minimal cross-linkage across or between scales of inquiry. We believe that this current state creates numerous barriers that are preventing the advancement of relevant science, practice, and policy. As such, we believe that it is necessary to amplify and reaffirm our collective understanding that these fields share common means of inquiry, differentiated only by the units of measure being utilized, their sources of data, and the manner in which they are executed. Therefore, in this perspective, we explore and focus attention on such commonalities and then present a conceptual framework that links constituent activities into an integrated model that we refer to as a precision healthcare system. The presentation of this framework is intended to provide the basis for the types of shared, broad-based, and descriptive language needed to reference and realize such a framework.

Indexed as

Delivery of Health CarePrecision MedicineHumansLanguageclinical transformationpersonalized medicinepopulation healthprecision healthprecision medicinepublic healthvalue-based carevalue-driven care

Identifiers

PMID32100012
PMCPMC7647305

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.