Evidence map›Paper›PMID 41860828›Full record

ArticlePLOS digital health2026

Impact of electronic health records on nursing workflow efficiency and predictive factors in Palestinian hospitals.

Fuad Farajalla, Mousa Farajallah, Nesreen Alqaissi, Mohammad Qtait, Zeenat Mousa Mesk

Abstract read
In one paragraph

Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

5 authors.

Fuad FarajallaPalestine Polytechnic University, Hebron, Palestine.ORCID https://orcid.org/0009-0007-2881-1533
Mousa FarajallahPalestine Polytechnic University, Hebron, Palestine.
Nesreen AlqaissiPalestine Polytechnic University, Hebron, Palestine.
Mohammad QtaitPalestine Polytechnic University, Hebron, Palestine.ORCID https://orcid.org/0000-0003-2414-7982
Zeenat Mousa MeskPalestine Polytechnic University, Hebron, Palestine.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electronic Health Records (EHRs) have revolutionized patient care and data management, but their integration may disrupt workflow. Palestine recently introduced EHRs in their hospitals, yet no local data exist on nursing workflow. This study aims to assess the impact of EHRs on workflow efficiency and associated factors among nurses with direct paper-to-EHR transition experience. A quantitative, cross-sectional study design was employed. A convenience sample of 185 nurses was recruited from medical and surgical wards across selected hospitals. Data were collected via a structured questionnaire and analyzed using SPSS version 29 using descriptive statistics and multiple linear regressions, with significance set at p < 0.05. A total of 185 nurses participated, with the majority aged 25-34 years (61.6%). Most had 5-10 years of experience (42.2%). Overall, 70% of nurses reported high or very high workflow efficiency with EHR use (M = 3.59, SD = 0.75). EHRs were perceived to improve access to patient information (63.2%), reduce documentation time (63.8%), and support teamwork and communication, although 50.8% reported workflow interruptions due to technical issues. Multiple regression identified EHR user-friendliness (β = 0.261, p < 0.001), training (β = 0.243, p = 0.024), technical support (β = 0.184, p = 0.005), and age (β = -0.223, p = 0.037) as significant predictors of workflow efficiency. EHRs positively influence nurses' workflow; transition-experienced nurses highlight usability and training as significant predictor factors. Enhancing these areas can optimize clinical performance.

Identifiers

PMID41860828
PMCPMC13004382

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Registered trials

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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.