Evidence map›Paper›PMID 38646414›Full record

SynthesisFrontiers in artificial intelligence2024

Interactive network visualization of opioid crisis research: a tool for reinforcing data linkage skills for public health policy researchers.

Olga Scrivner, Thuy Nguyen, Michael Ginda, Kosali Simon, Katy Börner

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in artificial intelligence, 2024. 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

5 authors.

Olga ScrivnerLuddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, United States.
Thuy NguyenSchool of Public Health, University of Michigan, Ann Arbor, MI, United States.
Michael GindaLuddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, United States.
Kosali SimonO'Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN, United States.
Katy BörnerLuddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Public health policy researchers face a persistent challenge in identifying and integrating relevant data, particularly in the context of the U.S. opioid crisis, where a comprehensive approach is crucial. Purpose: To meet this new workforce demand health policy and health economics programs are increasingly introducing data analysis and data visualization skills. Such skills facilitate data integration and discovery by linking multiple resources. Common linking strategies include individual or aggregate level linking (e.g., patient identifiers) in primary clinical data and conceptual linking (e.g., healthcare workforce, state funding, burnout rates) in secondary data. Often, the combination of primary and secondary datasets is sought, requiring additional skills, for example, understanding metadata and constructing interlinkages. Methods: To help improve those skills, we developed a 2-step process using a scoping method to discover data and network visualization to interlink metadata. Results: We show how these new skills enable the discovery of relationships among data sources pertinent to public policy research related to the opioid overdose crisis and facilitate inquiry across heterogeneous data resources. In addition, our interactive network visualization introduces (1) a conceptual approach, drawing from recent systematic review studies and linked by the publications, and (2) an aggregate approach, constructed using publicly available datasets and linked through crosswalks. Conclusions: These novel metadata visualization techniques can be used as a teaching tool or a discovery method and can also be extended to other public policy domains.

Indexed as

data explorationdata linkagedata visualizationnetwork visualizationpublic health policyskills

Identifiers

PMID38646414
PMCPMC11026550

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.