Evidence map›Paper›PMID 26957292›Full record

ArticleJournal of digital imaging2016

A Business Analytics Software Tool for Monitoring and Predicting Radiology Throughput Performance.

Stephen Jones, Seán Cournane, Niall Sheehy, Lucy Hederman

Abstract read
In one paragraph

Article in Journal of digital imaging, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. The Enterprise Imaging Value Proposition.Journal of digital imaging · 2020
    Review
  3. Article
  4. 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

4 authors.

Stephen JonesRéiteach Computer Systems, Anfield House, Baldonnell Business Park, Naas Road, Dublin 22, Ireland. stephen.jones@reiteach.ie.
Seán CournaneDiagnostic Imaging Department, St James's Hospital, Dublin 8, Ireland.
Niall SheehyDiagnostic Imaging Department, St James's Hospital, Dublin 8, Ireland.
Lucy HedermanTrinity College Dublin, College Green, Dublin 2, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Business analytics (BA) is increasingly being utilised by radiology departments to analyse and present data. It encompasses statistical analysis, forecasting and predictive modelling and is used as an umbrella term for decision support and business intelligence systems. The primary aim of this study was to determine whether utilising BA technologies could contribute towards improved decision support and resource management within radiology departments. A set of information technology requirements were identified with key stakeholders, and a prototype BA software tool was designed, developed and implemented. A qualitative evaluation of the tool was carried out through a series of semi-structured interviews with key stakeholders. Feedback was collated, and emergent themes were identified. The results indicated that BA software applications can provide visibility of radiology performance data across all time horizons. The study demonstrated that the tool could potentially assist with improving operational efficiencies and management of radiology resources.

Indexed as

Decision Support TechniquesRadiology Department, HospitalSoftwareQualitative ResearchRadiographyRadiologyRadiology Information SystemsAnalyticsBusiness analyticsBusiness intelligenceDecision supportDigital dashboardOLAPOperational efficienciesPredictive analysisWaiting lists

Identifiers

PMID26957292
PMCPMC5114222

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.