Evidence map›Paper›PMID 41191650›Full record

ArticlePloS one2025

Leveraging industry 4.0 technologies for healthcare innovation and efficiency.

Ricardo Santa, Thomas Tegethoff, Alvaro Moncada, Diego Morante

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Ricardo SantaColegio de Estudios Superiores de Administración-Cesa, Bogotá, Colombia.ORCID https://orcid.org/0000-0003-2584-2928
Thomas TegethoffColegio de Estudios Superiores de Administración-Cesa, Bogotá, Colombia.
Alvaro MoncadaColegio de Estudios Superiores de Administración-Cesa, Bogotá, Colombia.
Diego MoranteEscuela militar de aviación - Emavi, Cali, Colombia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the specific impacts of Industry 4.0 technologies-such as artificial intelligence, Internet of Things (IoT), and data-driven automation-on collaboration, communication, service efficiency, and organizational performance within high-complexity hospitals in Colombia. Despite growing global interest, empirical evidence from developing countries remains scarce. To address this gap, we conducted a survey involving 272 respondents-comprising administrative personnel, healthcare providers, and supply chain staff-across hospitals classified as Level III and IV in complexity under Colombian healthcare regulations. The data were analyzed using Structural Equation Modeling (SEM) to examine hypothesized relationships between technological innovation and operational variables. Results demonstrate that Industry 4.0 technologies significantly enhance internal collaboration and communication among stakeholders, contributing to improved organizational performance. However, the anticipated reduction in patient service time through technology adoption was not statistically supported, highlighting challenges in the integration and usability of these technologies. Barriers such as inadequate staff training, limited interoperability, and financial constraints were identified as critical obstacles. The model confirms the role of collaboration in reducing service times and underscores the need for targeted strategies to fully leverage technological investments. By articulating clear relationships and practical implications, this study offers evidence-based guidance for healthcare managers, policymakers, and technologists seeking to optimize the deployment of Industry 4.0 tools in resource-constrained healthcare environments..

Indexed as

Delivery of Health CareEfficiency, OrganizationalInventionsArtificial IntelligenceColombiaHealth PersonnelHumansInternet of ThingsSurveys and Questionnaires

Identifiers

PMID41191650
PMCPMC12588531

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.