Evidence map›Paper›PMID 29881751›Full record

ArticleEGEMS (Washington, DC)2017

Concordium 2016: Data and Knowledge Transforming Health.

Beth Devine

Abstract read
In one paragraph

Article in EGEMS (Washington, DC), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Beth DevineDepartment of Pharmaceutical Outcomes Research and Policy Program, Department of Health Services, Department of Biomedical Informatics, Department of Surgery at the University of Washington.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introduction and contextConcordium 2016 celebrated the potential for data and knowledge to transform health. Through a series of plenaries, presentations, workshops and demonstrations, the conference highlighted projects among four themes: effectiveness and outcomes research, health care analytics and operations, public and population health, and quality improvement. PAPERS IN THE SPECIAL ISSUE: The eight papers that comprise this special issue of CROSS-CUTTING ELEMENTS AND OVERLAPPING THEMES: Several of the papers contain elements of multiple overlapping themes. We integrate these into five overlapping themes: telehealth, user-centered design/usability, clinic workflow, patient-centered care, and population health management through prediction modeling and risk adjustment. CONCLUSION AND FUTURE DIRECTIONS: The effort to leverage all types of Big Data to improve health and healthcare is a monumental effort that will require the work of numerous stakeholders, and one that will unfold incrementally over time. This collection of eight papers reflects the current state of the art. Concordium 2017 will take a different form, inviting a small set of leaders in the field to focus on the next round of exciting and provocative research currently underway to improve the nation's health.

Indexed as

Concordium 2016learning health system

Identifiers

PMID29881751
PMCPMC5983075

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.