Evidence map›Paper›PMID 35220451›Full record

ArticleWorld journal of surgery2022

The Application of Human Factors Engineering to Reduce Operating Room Turnover in Robotic Surgery.

Tara N Cohen, Jennifer T Anger, Kevin Shamash, Kenneth R Catchpole, Raymund Avenido, Eric J Ley, Bruce L Gewertz, Daniel Shouhed

Abstract read
In one paragraph

Article in World journal of surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 19% 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, 10 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Tara N CohenDepartment of Surgery, Cedars-Sinai Medical Center, 8687 Melrose Ave., Suite G-555, West Hollywood, CA, 90069, USA. Tara.cohen@cshs.org.ORCID http://orcid.org/0000-0003-2137-6093
Jennifer T AngerDepartment of Urology, University of California San Diego, 9400 Campus Point Drive #7897, La Jolla, CA, 92037, USA.
Kevin ShamashDepartment of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Suite 8215NT, Los Angeles, CA, 90048, USA.
Kenneth R CatchpoleDepartment of Anesthesia, Medical University of South Carolina, Storm Eye Building, Ashley Avenue, Charleston, SC, 29425, USA.
Raymund AvenidoDepartment of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Suite 8215NT, Los Angeles, CA, 90048, USA.
Eric J LeyDepartment of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Suite 8215NT, Los Angeles, CA, 90048, USA.
Bruce L GewertzDepartment of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Suite 8215NT, Los Angeles, CA, 90048, USA.
Daniel ShouhedDepartment of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Suite 8215NT, Los Angeles, CA, 90048, USA.
Cedars-Sinai Medical Center · USMedical University of South Carolina · USUniversity of California San Diego · US

Funding

Human Factors and Systems Integration in High Technology Surgery (HF-SIgHTS)R01HS026491 · AHRQ · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI ANGER, JENNIFER TASH, CATCHPOLE, KEN · 2018 to 2022
$2.0M
Improving the Delivery of Robotic SurgeryR03EB017447 · NIBIB · CEDARS-SINAI MEDICAL CENTER · PI ANGER, JENNIFER TASH, CATCHPOLE, KEN · 2014 to 2015
$167k
AHRQ HHS R01 HS026491NIBIB NIH HHS R03 EB017447
6 · The paper itself

Abstract

backgroundChallenges associated with turnover time are magnified in robotic surgery. The introduction of advanced technology increases the complexity of an already intricate perioperative environment. We applied a human factors approach to develop systematic, data-driven interventions to reduce robotic surgery turnover time.

methodsResearchers observed 40 robotic surgery turnovers at a tertiary hospital [20 pre-intervention (Jan 2018 to Apr 2018), 20 post-intervention (Jan 2019 to Jun 2019)]. Components of turnover time, including cleaning, instrument and room set-up, robot preparation, flow disruptions, and major delays, were documented and analyzed. Surveys and focus groups were used to investigate staff perceptions of robotic surgery turnover time. A multidisciplinary team of human factors experts and physicians developed targeted interventions. Pre- and post-intervention turnovers were compared.

resultsMedian turnover time was 67 min (mean: 72, SD: 24) and 22 major delays were noted (1.1/case). The largest contributors were instrument setup (25.5 min) and cleaning (25 min). Interventions included an electronic dashboard for turnover time reporting, clear designation of roles and simultaneous completion of tasks, process standardization of operating room cleaning, and data transparency through monthly reporting. Post-intervention turnovers were significantly shorter (U = 57.5, p = .000) and ten major delays were noted.

conclusionsHuman factors analysis generated interventions to improve turnover time. Significant improvements were seen post-intervention with a reduction in turnover time by a 26 min and decrease in major delays by over 50%. Future opportunities to intervene and further improve turnover time include targeting pre- and post-operative care phases.

Indexed as

Operating RoomsRobotic Surgical ProceduresErgonomicsHumansPersonnel TurnoverTime Factors

Identifiers

PMID35220451
PMCPMC13157717
OpenAlexW4214733413

What OpenQuestion holds

Textmetadata
LicenceTDM
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.