Evidence map›Paper›PMID 28848627›Full record

ArticleElectronic physician2017

Geographic Information System (GIS) capabilities in traffic accident information management: a qualitative approach.

Maryam Ahmadi, Ali Valinejadi, Afshin Goodarzi, Ameneh Safari, Morteza Hemmat, Hesamedin Askari Majdabadi, Ali Mohammadi

Open access · goldAbstract read
In one paragraph

Article in Electronic physician, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.5field-weighted citation impact, top 12% of its field
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

3 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Review
  3. State-of-the-art review: preventing child and youth pedestrian motor vehicle collisions: critical issues and future directions.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2021
    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 at 4 institutions in 2 countries.

Maryam AhmadiPh.D. of Health Information Management, Professor, Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
Ali ValinejadiPh.D. of Health Information Management, Assistant Professor, Social Determinants of Health Research Center, Semnan University of Medical Sciences, Semnan, Iran.
Afshin GoodarziM.Sc. of Nursing, Department of Emergency Medicine, Faculty of Paramedics, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Ameneh SafariM.Sc. of Health Information Technology, Department of Research Management Office, Faculty of Paramedics, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Morteza HemmatPh.D. of Health Information Management, Assistant Professor, Department of Health Information Technology, School of Nursing, Saveh University of Medical Sciences, Saveh, Iran.
Hesamedin Askari MajdabadiPhD of Health, Assistant professor, Nursing care research center, Semnan University of Medical Sciences, Semnan, Iran.
Ali MohammadiPh.D. of Health Information Management, Assistant Professor, Department of Health Information Management, Faculty of Paramedics, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Health Information Management · BEKermanshah University of Medical Sciences · IRSemnan University of Medical Sciences · IRIran University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraffic accidents are one of the more important national and international issues, and their consequences are important for the political, economical, and social level in a country. Management of traffic accident information requires information systems with analytical and accessibility capabilities to spatial and descriptive data.

objectiveThe aim of this study was to determine the capabilities of a Geographic Information System (GIS) in management of traffic accident information.

methodsThis qualitative cross-sectional study was performed in 2016. In the first step, GIS capabilities were identified via literature retrieved from the Internet and based on the included criteria. Review of the literature was performed until data saturation was reached; a form was used to extract the capabilities. In the second step, study population were hospital managers, police, emergency, statisticians, and IT experts in trauma, emergency and police centers. Sampling was purposive. Data was collected using a questionnaire based on the first step data; validity and reliability were determined by content validity and Cronbach's alpha of 75%. Data was analyzed using the decision Delphi technique.

resultsGIS capabilities were identified in ten categories and 64 sub-categories. Import and process of spatial and descriptive data and so, analysis of this data were the most important capabilities of GIS in traffic accident information management.

conclusionStoring and retrieving of descriptive and spatial data, providing statistical analysis in table, chart and zoning format, management of bad structure issues, determining the cost effectiveness of the decisions and prioritizing their implementation were the most important capabilities of GIS which can be efficient in the management of traffic accident information.

Indexed as

AccidentsGeographic Information SystemInformation managementInformation SystemsTraffic

Identifiers

PMID28848627
PMCPMC5557132
OpenAlexW2738968032

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.