Evidence map›Paper›PMID 35928182›Full record

ArticleFuture healthcare journal2022

Surgical block 4.0: a digital intervention based on a real-time location patient-flow solution to support the automation of surgical pathways.

Jordi Rovira-Simón, Marc Sales-I-Coll, Patricia Pozo-Rosich, Juan Antonio Hueto-Madrid, Raquel Cánovas Paradell, Anna Ochoa de Echagüen Aguilar, Marta Carbonell-Cobo, Rodolfo de Castro, Genevieve Shaw

Abstract readCase Reports
In one paragraph

Article in Future healthcare journal, 2022. 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
–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

2 citing papers in PubMed.

  1. Review
  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

9 authors.

Jordi Rovira-SimónHospital Universitari Vall d'Hebron, Barcelona, Spain.
Marc Sales-I-CollUniversitat de Girona, Girona, Spain.
Patricia Pozo-RosichUniversitat Autònoma de Barcelona, Barcelona, Spain.
Juan Antonio Hueto-MadridHospital Universitari Vall d'Hebron, Barcelona, Spain.
Raquel Cánovas ParadellHospital Universitari Vall d'Hebron, Barcelona, Spain.
Anna Ochoa de Echagüen AguilarESSENTIA Health Management, Barcelona, Spain.
Marta Carbonell-CoboInstitut Català d'Oncologia, Barcelona, Spain.
Rodolfo de Castromanagement and product design, Universitat de Girona, Girona, Spain.
Genevieve ShawSaxlingham Nethergate, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As internet of things (IoT) technologies are increasingly adopted by healthcare and hospitals, new opportunities are emerging to transform patient pathways and achieve efficient delivery of care. This implemented project follows the drivers and requirements of industry 4.0, based on surgical process analysis and optimisation using IoT technology, with the goal of creating '4.0 hospitals'. Our study presents the implementation of a novel IoT application, aiming to give support to multidisciplinary surgical teams through the optimisation of patient pathways to facilitate the surgical process. The implemented solution is based on real-time location systems (RTLS) technology, a subgroup within IoT, and it originated through the hospital needing to address the sudden surge of surgical elective care demand. The solution also enhances patient safety, facilitates quality of care by increasing communication and reduces costs. This IoT tool has facilitated the increase of theatre utilisation from 70.02% to 82.5% in 2 years, which has translated into an increase of surgical activity capacity, with an impact on reducing the waiting list.

Indexed as

internet of thingspatient flowreal-time location solutionssurgical pathways automation

Identifiers

PMID35928182
PMCPMC9345239

What OpenQuestion holds

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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.