Evidence map›Paper›PMID 39161935›Full record

ArticleSAGE open nursing

Virtual Healthcare Revolution: Understanding Nurse Competencies and Roles.

Ibrahim Mubarak Al Baalharith, Ahmad Eissa Aboshaiqah

Abstract read
In one paragraph

Article in SAGE open nursing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

2 authors.

Ibrahim Mubarak Al BaalharithCollege of Nursing, King Saud University, Riyadh, Saudi Arabia.ORCID https://orcid.org/0000-0001-6210-4655
Ahmad Eissa AboshaiqahCollege of Nursing, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Digital healthcare, especially virtual health, has changed nurses' jobs and skills. In the evolving healthcare landscape, nurses healthcare landscape is increasingly required to have diverse competencies to navigate the world of virtual health effectively. Objective: This study aims to qualitatively explore the role of nurses in virtual health and the competencies required to work in virtual health in Saudi Arabia, with a specific focus on SEHA virtual hospital. Methods: An online open survey with nursing experts was employed as the qualitative method approach during the initial phase of an online Delphi study design. Results: Twelve core competencies were identified: digital technology proficiency, professionalism, clinical expertise, leadership, legal and ethical considerations, care coordination, documentation, effective communication, patient assessment and diagnosis, patient safety, patient-centered care, and remote patient monitoring. Conclusions: The research emphasizes the crucial role of nurses in virtual hospitals and clinics, contributing to the expansion of the virtual healthcare environment. It presents a thorough competency framework that can guide the development of training programs and policies, enhancing the effectiveness of virtual healthcare delivery. Impact: The study provides a foundational competencies list that can guide the development of comprehensive training programs for nurses in virtual healthcare. Policymakers and educational leaders are encouraged to use these findings to create standardized practices and policies, enhancing the effectiveness and efficiency of virtual healthcare delivery.

Indexed as

competenciesdigital technology proficiencynursespatient-centred careSaudi ArabiaSEHA Virtual Hospitalvirtual healthcare

Identifiers

PMID39161935
PMCPMC11331460

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.