Evidence map›Paper›PMID 36185391›Full record

ArticleDigital health

A randomized controlled trial for evaluating the impact of integrating a computerized clinical decision support system and a socially assistive humanoid robot into grand rounds during pre/post-operative care.

Izidor Mlakar, Urška Smrke, Vojko Flis, Andrej Bergauer, Nina Kobilica, Tadej Kampič, Samo Horvat, Damjan Vidovič, Bojan Musil, Nejc Plohl

Abstract read
In one paragraph

Article in Digital health. 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. 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

10 authors.

Izidor MlakarFaculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia.ORCID https://orcid.org/0000-0002-4910-1879
Urška SmrkeFaculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia.
Vojko FlisUniversity Clinical Centre Maribor, Maribor, Slovenia.
Andrej BergauerUniversity Clinical Centre Maribor, Maribor, Slovenia.
Nina KobilicaUniversity Clinical Centre Maribor, Maribor, Slovenia.
Tadej KampičUniversity Clinical Centre Maribor, Maribor, Slovenia.
Samo HorvatUniversity Clinical Centre Maribor, Maribor, Slovenia.
Damjan VidovičUniversity Clinical Centre Maribor, Maribor, Slovenia.
Bojan MusilFaculty of Arts, Department of Psychology, University of Maribor, Maribor, Slovenia.
Nejc PlohlFaculty of Arts, Department of Psychology, University of Maribor, Maribor, Slovenia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although clinical decision support systems (CDSSs) are increasingly emphasized as one of the possible levers for improving care, they are still not widely used due to different barriers, such as doubts about systems' performance, their complexity and poor design, practitioners' lack of time to use them, poor computer skills, reluctance to use them in front of patients, and deficient integration into existing workflows. While several studies on CDSS exist, there is a need for additional high-quality studies using large samples and examining the differences between outcomes following a decision based on CDSS support and those following decisions without this kind of information. Even less is known about the effectiveness of a CDSS that is delivered during a grand round routine and with the help of socially assistive humanoid robots (SAHRs). In this study, 200 patients will be randomized into a Control Group (i.e. standard care) and an Intervention Group (i.e. standard care and novel CDSS delivered via a SAHR). Health care quality and Quality of Life measures will be compared between the two groups. Additionally, approximately 22 clinicians, who are also active researchers at the University Clinical Center Maribor, will evaluate the acceptability and clinical usability of the system. The results of the proposed study will provide high-quality evidence on the effectiveness of CDSS systems and SAHR in the grand round routine.

Indexed as

Clinical decision support systemdigital health interventiongrand roundshealthcare qualityquality of lifesocially assistive humanoid robots

Identifiers

PMID36185391
PMCPMC9515524

What OpenQuestion holds

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LicenceCC BY
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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.