Evidence map›Paper›PMID 28855856›Full record

ArticlePerspectives in health information managemen2017

Determinant Factors in Applying Picture Archiving and Communication Systems (PACS) in Healthcare.

Mohammadhiwa Abdekhoda, Kawa Mirza Salih

Abstract read
In one paragraph

Article in Perspectives in health information managemen, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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.

Mohammadhiwa AbdekhodaIranian Center of Excellence in Health Management, at Tabriz University of Medical Sciences in Tabriz, Iran.
Kawa Mirza SalihDepartment of Charmo University in Sulaimani, Iraq.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesMeaningful use of picture archiving and communication systems (PACS) can change the workflow for accessing digital images, lead to faster turnaround time, reduce tests and examinations, and increase patient throughput. This study was carried out to identify determinant factors that affect the adoption of PACS by physicians.

methodsThis was a cross-sectional study in which 190 physicians working in a teaching hospital affiliated with Tehran University of Medical Sciences were randomly selected. Physicians' perceptions concerning the adoption of PACS were assessed by the conceptual path model of the Unified Theory of Acceptance and Use of Technology (UTAUT). Collected data were analyzed with regression analysis. Structural equation modeling was applied to test the final model that was developed.

resultsThe results show that the UTAUT model can explain about 61 percent of the variance on in the adoption of PACS (

conclusionsImplementation of new technology such as PACS in the healthcare sector is unavoidable. Our study clearly identified significant and nonsignificant factors that may affect the adoption of PACS. Also, this study acknowledged that physicians' perception is a key factor to manage the implementation of PACS optimally, and this fact should be considered by healthcare managers and policy makers.

Indexed as

Attitude of Health PersonnelAdultCross-Sectional StudiesFemaleHospitals, TeachingHumansIranMaleMiddle AgedPerceptionPhysiciansPsychological TheoryRadiology Information SystemsSocial Environmentphysician, structural equation modelingpicture archiving and communication systems (PACS)Unified Theory of Acceptance and Use of Technology (UTAUT)

Identifiers

PMID28855856
PMCPMC5559691

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.