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The Application of Human Factors Engineering to Reduce Operating Room Turnover in Robotic Surgery.
Cohen, Tara N; Anger, Jennifer T; Shamash, Kevin; Catchpole, Kenneth R; Avenido, Raymund; Ley, Eric J; Gewertz, Bruce L; Shouhed, Daniel.
Afiliação
  • Cohen TN; Department of Surgery, Cedars-Sinai Medical Center, 8687 Melrose Ave., Suite G-555, West Hollywood, CA, 90069, USA. Tara.cohen@cshs.org.
  • Anger JT; Department of Urology, University of California San Diego, 9400 Campus Point Drive #7897, La Jolla, CA, 92037, USA.
  • Shamash K; Department of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Suite 8215NT, Los Angeles, CA, 90048, USA.
  • Catchpole KR; Department of Anesthesia, Medical University of South Carolina, Storm Eye Building, Ashley Avenue, Charleston, SC, 29425, USA.
  • Avenido R; Department of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Suite 8215NT, Los Angeles, CA, 90048, USA.
  • Ley EJ; Department of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Suite 8215NT, Los Angeles, CA, 90048, USA.
  • Gewertz BL; Department of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Suite 8215NT, Los Angeles, CA, 90048, USA.
  • Shouhed D; Department of Surgery, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Suite 8215NT, Los Angeles, CA, 90048, USA.
World J Surg ; 46(6): 1300-1307, 2022 06.
Article em En | MEDLINE | ID: mdl-35220451
ABSTRACT

BACKGROUND:

Challenges 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.

METHODS:

Researchers 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.

RESULTS:

Median 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.

CONCLUSIONS:

Human 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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Salas Cirúrgicas / Procedimentos Cirúrgicos Robóticos Tipo de estudo: Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Salas Cirúrgicas / Procedimentos Cirúrgicos Robóticos Tipo de estudo: Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article