Evidence map›Paper›PMID 33521585›Full record

ReviewMayo Clinic proceedings. Innovations, quality & outcomes2021

Robotics in Simulated COVID-19 Patient Room for Health Care Worker Effector Tasks: Preliminary, Feasibility Experiments.

W David Freeman, Devang K Sanghavi, Masood S Sarab, Mary S Kindred, Elizabeth M Dieck, Suzanne M Brown, Tom Szambelan, Justin Doty, Brendan Ball, Heidi M Felix and 4 more

Open access · goldAbstract readReview
In one paragraph

Review in Mayo Clinic proceedings. Innovations, quality & outcomes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 9% of its field
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 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Use of Robots in Critical Care: Systematic Review.Journal of medical Internet research · 2022
    Pooled it
  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

14 authors at 4 institutions in 1 country.

W David FreemanDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL.
Devang K SanghaviDepartment of Critical Care Medicine, Mayo Clinic, Jacksonville, FL.
Masood S SarabDepartment of Nursing, Mayo Clinic, Jacksonville, FL.
Mary S KindredDepartment of Nursing, Mayo Clinic, Jacksonville, FL.
Elizabeth M DieckDepartment of Nursing, Mayo Clinic, Jacksonville, FL.
Suzanne M BrownDepartment of Nursing, Mayo Clinic, Jacksonville, FL.
Tom SzambelanCobot Team LLC, Portland, OR.
Justin DotyCobot Team LLC, Portland, OR.
Brendan BallCobot Team LLC, Portland, OR.
Heidi M FelixHospital Internal Medicine, Mayo Clinic, Jacksonville, FL.
Jesse C DoveMedical Simulation Center, Mayo Clinic, Jacksonville, FL.
Jorge M MalleaDivision of Pulmonary, Allergy and Sleep Medicine, Mayo Clinic, Jacksonville, FL.
Christy SoaresFlorida State University College of Medicine, Tallahassee.
Leslie V SimonDepartment of Emergency Medicine, Mayo Clinic, Jacksonville, FL.
Jacksonville College · USWinnMed · USMayo Clinic in Florida · USFlorida State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has strained health care systems and personal protective equipment (PPE) supplies globally. We hypothesized that a collaborative robot system could perform health care worker effector tasks inside a simulated intensive care unit (ICU) patient room, which could theoretically reduce both PPE use and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposures. We planned a prospective proof-of-concept feasibility and design pilot study to test 5 discrete medical tasks in a simulated ICU room of a COVID-19 patient using a collaborative robot: push a button on intravenous pole machine when alert occurs for downstream occlusion, adjust ventilator knob, push button on ICU monitor to silence false alerts, increase oxygen flow on wall-mounted flow meter to allow the patient to walk to the bathroom and back (dial-up and dial-down oxygen flow), and push wall-mounted nurse call button. Feasibility was defined as task completion robotically. A training period of 45 minutes to 1 hour was needed to program the system de novo for each task. In less than 30 days, the team completed 5 simple effector task experiments robotically. Selected collaborative robotic effector tasks appear feasible in a simulated ICU room of the COVID-19 patient. Theoretically, this robotic approach could reduce PPE use and staff SARS-CoV-2 exposure. It requires future validation and health care worker learning similar to other ICU device training.

Indexed as

COVID-19, coronavirus disease 2019HCW, health care workerICU, intensive care unitIV, intravenousPPE, personal protective equipment

Identifiers

PMID33521585
PMCPMC7833738
OpenAlexW3111294708

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.