Evidence map›Paper›PMID 33447098›Full record

ArticleOpen access emergency medicine : OAEM2020

Mobile Ambulatory Application Asafny and Traditional Phone Request 997: A Comparative Cross-Sectional Study.

Arwa Althumairi, Zainab Alnasser, Sarah Alsadeq, Nouf Al-Kahtani, Afnan Aljaffary

Abstract read
In one paragraph

Article in Open access emergency medicine : OAEM, 2020. 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. Review
  2. Observational
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.

Arwa AlthumairiHealth Information Management and Technology (HIMT) Department, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.ORCID 0000-0002-0371-408X
Zainab AlnasserHealth Information Management and Technology (HIMT) Department, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.ORCID 0000-0003-3748-6086
Sarah AlsadeqHealth Information Management and Technology (HIMT) Department, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.ORCID 0000-0002-9367-7429
Nouf Al-KahtaniHealth Information Management and Technology (HIMT) Department, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.ORCID 0000-0003-0211-5461
Afnan AljaffaryHealth Information Management and Technology (HIMT) Department, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.ORCID 0000-0001-6656-3306

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to determine whether there was a time difference between the ambulatory application Asafny and traditional type 997 in reaching people in need and interacting appropriately. MATERIALS AND

methodsThis study was conducted using retrospective cross-sectional study. A total of 2120 ambulance requests was extracted from Saudi Red Crescent Authority servers in Eastern Province, Kingdom of Saudi Arabia. The requests were extracted between 2017 and 2019.

resultsThere were no significant differences between the two methods of request. In 2019, the shortest times for all phases of requests were recorded. "Ordinary patient" was the most common cause for requests.

conclusionOver the years, efforts by the Saudi Red Crescent Authority facilitated improvements in ambulatory services by adapting new technology and services. This has helped reduce times for all phases of emergency requests.

Indexed as

997ambulancesAsafnyemergency servicehospitalmobile applicationsreaction timeRed CrossSaudi ArabiaSaudi Red Crescent Authority

Identifiers

PMID33447098
PMCPMC7801914

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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.