Evidence map›Paper›PMID 28265450›Full record

ReviewDisaster and military medicine2016

Learning lessons in emergency management: the 4th International Conference on Healthcare System Preparedness and Response to Emergencies and Disasters.

B Adini, A Ohana, E Furman, R Ringel, Y Golan, E Fleshler, U Keren, S Reisner

Abstract readReview
In one paragraph

Review in Disaster and military medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Level of emergency and disaster preparedness of public hospitals in Northwest Ethiopia: A cross-sectional study.African journal of emergency medicine : Revue africaine de la medecine d'urgence · 2022
    Article
  3. Review
  4. Article
  5. Maintaining Preparedness to Severe Though Infrequent Threats-Can It Be Done?International journal of environmental research and public health · 2020
    Article
  6. 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

8 authors.

B AdiniEmergency and Disaster Management Division, Ministry of Health, Igal Alon 119, Tel Aviv, Israel.
A OhanaHome Front Command, Ramla, Israel.
E FurmanHome Front Command, Ramla, Israel.
R RingelEmergency and Disaster Management Division, Ministry of Health, Igal Alon 119, Tel Aviv, Israel.
Y GolanHome Front Command, Ramla, Israel.
E FleshlerHome Front Command, Ramla, Israel.
U KerenEmergency and Disaster Management Division, Ministry of Health, Igal Alon 119, Tel Aviv, Israel.
S ReisnerRambam Medical Center, Haifa, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe International Preparedness & Response to Emergencies & Disasters (IPRED) conferences are conducted bi-annually in order to share insights and lessons learned from diverse crises. The aim of the article is to bring the IPRED conferences into better professional attention and to share the main insights that were presented in IPRED IV, which was held in January 2016. MAIN BODY: The major lessons learned included:

conclusionsIPRED conferences provide a platform for sharing insights and lessons learned from diverse emergencies and disasters. The conferences offer a unique opportunity to share knowledge aimed at improving emergency preparedness, networking between various parties, and substantiates the knowledge and experience of all professionals who take part in the proceedings.

Indexed as

Animal shelteringCivil–military cooperationDisastersEmergency managementHumanitarian actionLessons learnedResilienceTraining and exercises

Identifiers

PMID28265450
PMCPMC5330161

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.