Evidence map›Paper›PMID 38204626›Full record

ArticleJTCVS open2023

Remote telemonitoring is associated with improved patient safety and decreased workload of nurses.

Marijana Zubrinic, Lauren Vrbanic, Shaf Keshavjee

Abstract read
In one paragraph

Article in JTCVS open, 2023. 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.

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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

3 authors.

Marijana ZubrinicDivision of Thoracic Surgery, Sprott Department of Surgery, Toronto General Hospital, Toronto, Ontario, Canada.
Lauren VrbanicTrinity College, Dublin, Ireland.
Shaf KeshavjeeDivision of Thoracic Surgery, University Health Network, University of Toronto, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: There is significant interest in exploring new technologies to improve efficiency and work-life quality for nurses. We aimed to evaluate the impact of a remote video monitoring (RVM) solution that provides continuous in-hospital patient audio-video (AV) monitoring by technicians. Methods: The RVM system that we developed, consisting of 2-way AV communication and a continuous O Results: Data were collected from April 2020 to May 2022. A total of 2087 patients were monitored at 5 hospital sites. The technicians identified 54,716 safety concerns that required them to intervene remotely and address with the patient. Of these, 46,289 required escalation of nursing staff, who were called to the bedside through the RVM alerting technology. Importantly, 8427 safety concerns were managed solely by the technicians without the need for nursing intervention, resulting in 8427 avoided nursing visits to the bedside. The surveyed nurses reported that the RVM technology provided reassurance that additional support was available to assist them in managing their patients. Patients and their families also expressed high degree of satisfaction. Since implementation, the rates of falls and other adverse events have been reduced, with the greatest impact in patients on high-flow oxygen. Code blue and mortality rates decreased from 7% to 1%. Conclusions: The use of RVM has proven to be a successful innovation at our hospital and has led to improved patient safety. RVM was able to reduce 8427 individual nurse visits to the bedside, allowing nurses to manage the care of patients more effectively while improving both patient and staff satisfaction.

Indexed as

healthcare efficiencyjob satisfactionnurse workloadpatient safetyperioperative managementremote monitoring

Identifiers

PMID38204626
PMCPMC10775035

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.