Advertisement

Surgical Endoscopy

, Volume 30, Issue 9, pp 3749–3761 | Cite as

Safety, efficiency and learning curves in robotic surgery: a human factors analysis

  • Ken CatchpoleEmail author
  • Colby Perkins
  • Catherine Bresee
  • M. Jonathon Solnik
  • Benjamin Sherman
  • John Fritch
  • Bruno Gross
  • Samantha Jagannathan
  • Niv Hakami-Majd
  • Raymund Avenido
  • Jennifer T. Anger
Article

Abstract

Background

Expense, efficiency of use, learning curves, workflow integration and an increased prevalence of serious incidents can all be barriers to adoption. We explored an observational approach and initial diagnostics to enhance total system performance in robotic surgery.

Methods

Eighty-nine robotic surgical cases were observed in multiple operating rooms using two different surgical robots (the S and Si), across several specialties (Urology, Gynecology, and Cardiac Surgery). The main measures were operative duration and rate of flow disruptions—described as ‘deviations from the natural progression of an operation thereby potentially compromising safety or efficiency.’ Contextual parameters collected were surgeon experience level and training, type of surgery, the model of robot and patient factors. Observations were conducted across four operative phases (operating room pre-incision; robot docking; main surgical intervention; post-console).

Results

A mean of 9.62 flow disruptions per hour (95 % CI 8.78–10.46) were predominantly caused by coordination, communication, equipment and training problems. Operative duration and flow disruption rate varied with surgeon experience (p = 0.039; p < 0.001, respectively), training cases (p = 0.012; p = 0.007) and surgical type (both p < 0.001). Flow disruption rates in some phases were also sensitive to the robot model and patient characteristics.

Conclusions

Flow disruption rate is sensitive to system context and generates improvement diagnostics. Complex surgical robotic equipment increases opportunities for technological failures, increases communication requirements for the whole team, and can reduce the ability to maintain vision in the operative field. These data suggest specific opportunities to reduce the training costs and the learning curve.

Keywords

Robotic surgery Human Factors Error Safety Teamwork Automation 

Notes

Acknowledgments

This was funded by National Institute of Biomedical Imaging & Biomedical Engineering Award R03EB017447 (Catchpole/Anger) and the UCLA Medical Student Training in Aging Research Program- the National Institute on Aging (T35AG026736), the John A. Hartford Foundation, and the Lillian R. Gleitsman Foundation. Our sincere thanks to all the surgeons, OR staff and residents who participated and allowed us to observe their operations.

Compliance with ethical standards

Disclosures

Dr. Catchpole has received funding from Medtronic Ltd, and received funding to attend a meeting unrelated to this project at Intuitive Surgical headquarters. Colby Perkins, Catherine Bresee, M. Jonathon Solnik, Benjamin Sherman, John Fritchhas, Bruno Grosshas, Samantha Jagannathan, Niv Hakami-Majdhas, Raymund Avenido and Jennifer T. Anger: None.

References

  1. 1.
    Anger JT, Mueller ER, Tarnay C et al (2014) Robotic compared with laparoscopic sacrocolpopexy: a randomized controlled trial. Obstet Gynecol 123(1):5–12CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Barbash GI, Glied SA (2010) New technology and health care costs–the case of robot-assisted surgery. N Engl J Med 363(8):701–704CrossRefPubMedGoogle Scholar
  3. 3.
    Yule S, Flin R, Paterson-Brown S, Maran N, Rowley D (2006) Development of a rating system for surgeons’ non-technical skills. Med Educ 40(11):1098–1104CrossRefPubMedGoogle Scholar
  4. 4.
    Carayon P, Schoofs HA, Karsh BT et al. (2006) Work system design for patient safety: the SEIPS model. Qual.Saf Health Care 15 Suppl 1 (1475–3898 (Linking)):i50–i58Google Scholar
  5. 5.
    Woods D, Sarter N, Billings C (1997) Automation surprises. In: Gavriel Salvendy (ed) The handbook of human factors, 2nd edn. New York, John Wiley & Sons, Inc.Google Scholar
  6. 6.
    Loftus T, Dahl D, OHare B et al. (2015) Implementing a standardized safe surgery program reduces serious reportable events. J Am Coll Surg 220(1):12–17.e13Google Scholar
  7. 7.
    Sudan R, Bennett KM, Jacobs DO, Sudan DL (2012) Multifactorial analysis of the learning curve for robot-assisted laparoscopic biliopancreatic diversion with duodenal switch. Ann Surg 255(5):940–945CrossRefPubMedGoogle Scholar
  8. 8.
    Cook RI, Woods DD (1996) Adapting to new technology in the operating room. Hum Factors 38(4):593–613CrossRefPubMedGoogle Scholar
  9. 9.
    Catchpole KR, Giddings AE, de Leval MR et al (2006) Identification of systems failures in successful paediatric cardiac surgery. Ergonomics 49(5–6):567–588CrossRefPubMedGoogle Scholar
  10. 10.
    Catchpole KR, Giddings AE, Wilkinson M, Hirst G, Dale T, de Leval MR (2007) Improving patient safety by identifying latent failures in successful operations. Surgery 142(1):102–110CrossRefPubMedGoogle Scholar
  11. 11.
    McCulloch P, Mishra A, Handa A, Dale T, Hirst G, Catchpole K (2009) The effects of aviation-style non-technical skills training on technical performance and outcome in the operating theatre. Qual Saf Health Care 18(2):109–115CrossRefPubMedGoogle Scholar
  12. 12.
    Mishra A, Catchpole K, Dale T, McCulloch P (2008) The influence of non-technical performance on technical outcome in laparoscopic cholecystectomy. Surg Endosc 22(1):68–73CrossRefPubMedGoogle Scholar
  13. 13.
    Catchpole K, Ley E, Wiegmann D et al (2014) A human factors subsystems approach to trauma care. JAMA Surg 149(9):962–968CrossRefPubMedGoogle Scholar
  14. 14.
    Shouhed D, Blocker R, Gangi A, Ley E, Blaha J, Gewertz B, Wiegmann D, Starnes B, Karl C, Karl R, Margulies D, Catchpole K (2014). Flow Disruptions During Trauma Care. World J Surg 38(2):314–21. doi: 10.1007/s00268-013-2306-0 CrossRefPubMedGoogle Scholar
  15. 15.
    Wiegmann DA, Elbardissi AW, Dearani JA, Daly RC, Sundt TM (2007) Disruptions in surgical flow and their relationship to surgical errors: an exploratory investigation. Surgery 142(5):658–665CrossRefPubMedGoogle Scholar
  16. 16.
    Gurses AP, Kim G, Martinez EA et al (2012) Identifying and categorising patient safety hazards in cardiovascular operating rooms using an interdisciplinary approach: a multisite study. BMJ Qual Saf 21(10):810–818CrossRefPubMedGoogle Scholar
  17. 17.
    Henrickson SE, Wadhera RK, Elbardissi AW, Wiegmann DA, Sundt TM (2009) Development and pilot evaluation of a preoperative briefing protocol for cardiovascular surgery. J Am Coll Surg 208(6):1115–1123CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Catchpole KR, Gangi A, Blocker RC et al (2013) Flow disruptions in trauma care handoffs. J Surg Res 184(1):586–591CrossRefPubMedGoogle Scholar
  19. 19.
    Parker SE, Laviana AA, Wadhera RK, Wiegmann DA, Sundt TM (2010) Development and evaluation of an observational tool for assessing surgical flow disruptions and their impact on surgical performance. World J Surg 34(2):353–361CrossRefPubMedGoogle Scholar
  20. 20.
    Shouhed D, Blocker R, Gangi A et al (2014) Flow disruptions during trauma care. World J Surg 38(2):314–321CrossRefPubMedGoogle Scholar
  21. 21.
    Anger JT, Blocker R, Fritch J et al (2013) Surgical technique: just one part of the learning curve in robotic pelvic surgery. Neurourol Urodyn 32(2):150–151Google Scholar
  22. 22.
    Catchpole KR, Giddings AE, Hirst G, Dale T, Peek GJ, de Leval MR (2008) A method for measuring threats and errors in surgery. Cogn Technol Work 10(4):295–304CrossRefGoogle Scholar
  23. 23.
    Nayyar R, Gupta NP (2010) Critical appraisal of technical problems with robotic urological surgery. BJU Int 105(12):1710–1713CrossRefPubMedGoogle Scholar
  24. 24.
    Catchpole K, Mishra A, Handa A, McCulloch P (2008) Teamwork and error in the operating room: analysis of skills and roles. Ann Surg 247(4):699–706CrossRefPubMedGoogle Scholar
  25. 25.
    Catchpole KR (2011) Task, team and technology integration in the paediatric cardiac operating room. Prog Pediatr Cardiol 32:85–88CrossRefGoogle Scholar
  26. 26.
    Shouhed D, Catchpole K, Ley EJ et al (2012) Flow disruptions during trauma care. J Am Coll Surg 215(3):S99–S100CrossRefGoogle Scholar
  27. 27.
    Carthey J, de Leval MR, Reason JT (2001) The human factor in cardiac surgery: errors and near misses in a high technology medical domain. Ann Thorac Surg 72(1):300–305CrossRefPubMedGoogle Scholar
  28. 28.
    Morgan L, Robertson E, Hadi M, Catchpole K, Pickering S, New S, Collins G, McCulloch P (2013) Capturing intraoperative process deviations using a direct observational approach: the glitch method. BMJ Open 3(11):e003519. doi: 10.1136/bmjopen-2013-003519 CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    de Leval MR, Carthey J, Wright DJ, Reason JT (2000) Human factors and cardiac surgery: a multicenter study. J Thorac Cardiovasc Surg 119(4):661–672CrossRefPubMedGoogle Scholar
  30. 30.
    Catchpole K (2010) Errors in the operating theatre–how to spot and stop them. J Health Serv Res Policy 15 Suppl 1(1355–8196 (Linking)):48–51Google Scholar
  31. 31.
    Catchpole K, Godden PJ, Giddings AEB et al. (2005) Identifying and reducing errors in the operating theatre. Patient Safety Research Programme. Available at http://pcpoh.bham.ac.uk/publichealth/psrp/publications.htm. PS012
  32. 32.
    Dekker SW (2002) The field guide to human error investigations, vol 1. Ashgate, AldershotGoogle Scholar
  33. 33.
    Greenberg CC, Regenbogen SE, Studdert DM et al (2007) Patterns of communication breakdowns resulting in injury to surgical patients. J Am Coll Surg 204(4):533–540CrossRefPubMedGoogle Scholar
  34. 34.
    Catchpole K, Mishra A, Handa A, McCulloch P (2008) Teamwork and error in the operating room—analysis of skills and roles. Ann Surg 247(4):699–706CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Ken Catchpole
    • 1
    Email author
  • Colby Perkins
    • 1
    • 2
  • Catherine Bresee
    • 3
  • M. Jonathon Solnik
    • 4
  • Benjamin Sherman
    • 5
  • John Fritch
    • 5
  • Bruno Gross
    • 5
  • Samantha Jagannathan
    • 5
  • Niv Hakami-Majd
    • 5
  • Raymund Avenido
    • 1
  • Jennifer T. Anger
    • 1
  1. 1.Department of SurgeryCedars-Sinai Medical CenterLos AngelesUSA
  2. 2.David Geffen School of MedicineUniversity of CaliforniaLos AngelesUSA
  3. 3.Biostatistics and Bioinformatics Research InstituteCedars-Sinai Medical CenterLos AngelesUSA
  4. 4.Department of Obstetrics and GynecologyCedars-Sinai Medical CenterLos AngelesUSA
  5. 5.Medical Student Training in Aging Research (MSTAR) ProgramUniversity of CaliforniaLos AngelesUSA

Personalised recommendations