Evidence map›Paper›PMID 37288316›Full record

ArticleInternational journal of industrial ergonomics2023

Establishment-level occupational safety analytics: Challenges and opportunities.

Anne M Foreman, Jonathan E Friedel, Timothy D Ludwig, Maira E Ezerins, Yalçin Açikgöz, Shawn M Bergman, Oliver Wirth

Abstract read
In one paragraph

Article in International journal of industrial ergonomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

7 authors.

Anne M ForemanNational Institute for Occupational Safety and Health, USA.
Jonathan E FriedelNational Institute for Occupational Safety and Health, USA.
Timothy D LudwigAppalachian State University, USA.
Maira E EzerinsUniversity of Arkansas, USA.
Yalçin AçikgözAppalachian State University, USA.
Shawn M BergmanAppalachian State University, USA.
Oliver WirthNational Institute for Occupational Safety and Health, USA.

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

In occupational safety and health, big data and analytics show promise for the prediction and prevention of workplace injuries. Advances in computing power and analytical methods have allowed companies to reveal insights from the "big" data that previously would have gone undetected. Despite the promise, occupational safety has lagged behind other industries, such as supply chain management and healthcare, in terms of exploiting the potential of analytics and much of the data collected by organizations goes unanalyzed. The purpose of the present paper is to argue for the broader application of establishment-level safety analytics. This is accomplished by defining the terms, describing previous research, outlining the necessary components required, and describing knowledge gaps and future directions. The knowledge gaps and future directions for research in establishment-level analytics are categorized into readiness for analytics, analytics methods, technology integration, data culture, and impact of analytics.

Indexed as

Big dataData cultureInjuriesNear missesOccupational safetySafety analytics

Identifiers

PMID37288316
PMCPMC10242415

What OpenQuestion holds

Textmetadata
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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.