Evidence map›Paper›PMID 32850044›Full record

ArticleJournal of community hospital internal medicine perspectives2020

Understanding the means of communication between nurses and resident physicians in the modern world: A community-based university hospital survey results.

Tarek Haykal, Ragheed Al-Dulaimi, Shima Sidahmed, Ravi Velagapudi, Noelle Fahr, Seif Saeed, Ghassan Bachuwa

Open access · goldAbstract read
In one paragraph

Article in Journal of community hospital internal medicine perspectives, 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
1.3field-weighted citation impact, top 13% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 2 institutions in 1 country.

Tarek HaykalDepartment of Internal Medicine, Hurley Medical Center, Flint, Michigan.ORCID 0000-0002-8637-7292
Ragheed Al-DulaimiDepartment of Internal Medicine, Hurley Medical Center, Flint, Michigan.
Shima SidahmedDepartment of Internal Medicine, Hurley Medical Center, Flint, Michigan.
Ravi VelagapudiDepartment of Internal Medicine, Hurley Medical Center, Flint, Michigan.
Noelle FahrDepartment of Nursing, Hurley Medical Center, Flint, Michigan.
Seif SaeedDepartment of Internal Medicine, Hurley Medical Center, Flint, Michigan.
Ghassan BachuwaDepartment of Internal Medicine, Hurley Medical Center, Flint, Michigan.
Hurley Medical Center · USUniversity of Utah · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In a hospital setting, nurses and physicians are the two main caregivers for admitted patients. Their communication is an important driver of positive teamwork and ensures proper patient safety and a high level of patient care. In a hospital with a large internal medicine residency program, where the main communication between nurses and residents is by phone calls, the excess number of phone calls received, especially for non-urgent patient-related matters, can be disruptive and cause fatigue and burnout. Alternative means of communication have been reported, namely using the electronic medical records to try and create new means of communication and to decrease the burden of direct communication for non-urgent matters. This manuscript describes the results of a survey administered in an attempt to understand the communication between residents and nurses in the setting of a new communication tool created within the electronic medical records.

Indexed as

communicationE-messagingnurseresidents

Identifiers

PMID32850044
PMCPMC7425613
OpenAlexW3028014987

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.