Requirements for the structured recording of surgical device data in the digital operating room

Review Article

Abstract

Purpose

   Due to the increasing complexity of the surgical working environment, increasingly technical solutions must be found to help relieve the surgeon. This objective is supported by a structured storage concept for all relevant device data.

Methods

   In this work, we present a concept and prototype development of a storage system to address intraoperative medical data. The requirements of such a system are described, and solutions for data transfer, processing, and storage are presented. In a subsequent study, a prototype based on the presented concept is tested for correct and complete data transmission and storage and for the ability to record a complete neurosurgical intervention with low processing latencies. In the final section, several applications for the presented data recorder are shown.

Results

   The developed system based on the presented concept is able to store the generated data correctly, completely, and quickly enough even if much more data than expected are sent during a surgical intervention.

Conclusions

   The Surgical Data Recorder supports automatic recognition of the interventional situation by providing a centralized data storage and access interface to the OR communication bus. In the future, further data acquisition technologies should be integrated. Therefore, additional interfaces must be developed. The data generated by these devices and technologies should also be stored in or referenced by the Surgical Data Recorder to support the analysis of the OR situation.

Keywords

Computer-assisted surgery Workflow  Information system Surgical process model Intraoperative monitoring Data recording 

Notes

Acknowledgments

ICCAS is funded by the German Federal Ministry of Education and Research (BMBF) and the Saxon Ministry of Science and Fine Arts (SMWK) in the scope of the Unternehmen Region with grant number 03Z1LN12 and by the European Regional Development Fund (ERDF) and the state of Saxony within the frame of measures to support the technology sector.

Conflict of Interest

None.

References

  1. 1.
    Sackett DL (1997) Evidence-based medicine. Semin Perinatol 21:3–5PubMedCrossRefGoogle Scholar
  2. 2.
    Neumuth T, Liebmann P, Wiedemann P, Meixensberger J (2012) Surgical workflow management schemata for cataract procedures. Process model-based design and validation of workflow schemata. Methods Inf Med 51:371–382PubMedCrossRefGoogle Scholar
  3. 3.
    Ikuta K, Kato T, Ooe H (2008) Surgery recorder system aquiring position/force information of surgical forceps. In: Automation congress, WAC, pp 1–6Google Scholar
  4. 4.
    Kato T, Ikuta K (2008) Surgery recorder system for objective clinical accident investigation with digitized surgery procedures. In: The international conference on electrical engineeringGoogle Scholar
  5. 5.
    Bohn S, Franke S, Burgert O, Meixensberger J, Lindner D (2011) First clinical application of an open standards based OR integration system. Biomed Tech 56:2Google Scholar
  6. 6.
    Aggarwal R, Grantcharov T, Moorthy K, Milland T, Papasavas P, Dosis A, Bello F, Darzi A (2007) An evaluation of the feasibility, validity, and reliability of laparoscopic skills assessment in the operating room. Ann Surg 245:992–999PubMedCrossRefGoogle Scholar
  7. 7.
    Cone SW, Leung A, Mora F, Rafiq A, Merrell RC (2006) Multimedia data capture and management for surgical events: evaluation of a system. Telemed J E Health 12:351–358PubMedCrossRefGoogle Scholar
  8. 8.
    Guerlain S, Adams R, Turrentine B, Shin T, Guo H, Collins S, Calland F (2005) Assessing team performance in the operating room: development and use of a ‘black-box’ recorder and other tools for the intraoperative environment. J Am Coll Surg 200:29–37Google Scholar
  9. 9.
    Documet J, Le A, Liu B, Chiu J, Huang H (2010) A multimedia electronic patient record (ePR) system for image-assisted minimally invasive spinal surgery. Int J Comput Assist Radiol Surg 5:195–209PubMedCentralPubMedCrossRefGoogle Scholar
  10. 10.
    Barrs DM, Fukushima T, McElveen JT Jr (2001) Digital camera documentation system for facial nerve outcome assessment. Otol Neurotol 22:928–930PubMedCrossRefGoogle Scholar
  11. 11.
    Wurnig PN, Hollaus PH, Wurnig CH, Wolf RK, Ohtsuka T, Pridun NS (2003) A new method for digital video documentation in surgical procedures and minimally invasive surgery. Surg Endosc 17:232–235PubMedCrossRefGoogle Scholar
  12. 12.
    Healey AN (2004) Developing observational measures of performance in surgical teams. Qual Saf Health Care 13:33–40CrossRefGoogle Scholar
  13. 13.
    Reader TW, Flin R, Mearns K, Cuthbertson BH (2009) Developing a team performance framework for the intensive care unit. Crit Care Med 37:1787–1793PubMedCrossRefGoogle Scholar
  14. 14.
    Guerlain S, Shin T, Guo H, Adams R, Calland JF (2002) A Team Performance Data Collection and Analysis System. Proc Hum Factors Ergonom Soc Annu Meet 46:1443–1447CrossRefGoogle Scholar
  15. 15.
    Beckmann CRB, Lipscomb CH, Ling FW, Beckmann CA, Johnson H, Barton L, Computer-assisted video evaluation of surgical skills. Obstet Gynecol 85:1039–1041Google Scholar
  16. 16.
    Eubanks TR, Clements RH, Pohl D, Williams N, Schaad DC, Horgan S, Pellegrini C (1999) An objective scoring system for laparoscopic cholecystectomy. J Am Coll Surg 189:566–574PubMedCrossRefGoogle Scholar
  17. 17.
    Dath D, Regehr G, Birch D, Schlachta C, Poulin E, Mamazza J, Reznick R, MacRae HM (2004) Toward reliable operative assessment: the reliability and feasibility of videotaped assessment of laparoscopic technical skills. Surg Endosc 18:1800–1804PubMedCrossRefGoogle Scholar
  18. 18.
    Lee JY, Mucksavage P, Kerbl DC, Huynh VB, Etafy M, McDougall EM (2012) Validation study of a virtual reality robotic simulator-role as an assessment tool? J Urol 187:998–1002PubMedCrossRefGoogle Scholar
  19. 19.
    Dosis A, Aggarwal R, Bello F, Moorthy K, Munz Y, Gillies D, Darzi A (2005) Synchronized video and motion analysis for the assessment of procedures in the operating theater. Arch Surg 140:293–299PubMedCrossRefGoogle Scholar
  20. 20.
    Dosis A, Bello F, Rockall T, Munz Y, Moorthy K, Martin S, Darzi A (2003) ROVIMAS: a software package for assessing surgical skills using the da Vinci telemanipulator system. In: Information Technology Applications in Biomedicine, 4th Int IEEE EMBS Special Topic Conference on, pp 326–329Google Scholar
  21. 21.
    Bhatia B, Oates T, Xiao X, Hu P (2007) Real-time identification of operating room state from video. In: Proceedings of the 19th Natl Conf on Innov Appl of, Artif Intell, pp 1761–1766Google Scholar
  22. 22.
    Houliston BR, Parry DT, Merry AF (2011) TADAA: towards automated detection of anaesthetic activity. Methods Inf Med 50:464–471PubMedCrossRefGoogle Scholar
  23. 23.
    Neumuth T, Jannin P, Strauss G, Meixensberger J, Burgert O (2009) Validation of knowledge acquisition for surgical process models. J Am Med Inform Assoc 16:72–80Google Scholar
  24. 24.
    Cleary K, Mun SK (2004) OR2020 The Operating Room of the Future. In: OR2020 The Operating Room of the Future, Workshop ReportGoogle Scholar
  25. 25.
    Satava RM (2003) Disruptive visions. Surg Endosc 17:104–107PubMedCrossRefGoogle Scholar
  26. 26.
    Lemke HU, Vannier MW (2006) The operating room and the need for an IT infrastructure and standards. Int J CARS 1:117–121CrossRefGoogle Scholar
  27. 27.
    Goldman JM, Schrenker RA, Jackson JL, Whitehead SF (2005) Plug-and-play in the operating room of the future. Biomed Instrum Technol 39:194–199PubMedGoogle Scholar
  28. 28.
    Bohn S, Gessat M, Franke S, Voruganti A, Burgert O (2009) An integrated OR system based on open standards, http://hdl.handle.net/10380/3081, Accessed 19 March 2013
  29. 29.
    Tooley M, Wyatt D (2009) Aircraft electrical and electronic systems: principles, operation and maintenance. Elsevier, OxfordGoogle Scholar
  30. 30.
    International Telecommunication Union, G.764: Packetization guide. [Online]. Available: http://www.itu.int/rec/T-REC-G.764-199511-I!AppI/en. Accessed 19 March 2013
  31. 31.
    Rockstroh M, Franke S, Neumuth T (2013) A workflow-driven surgical information source management, CARS 2013, accepted for oral presentationGoogle Scholar
  32. 32.
    Franke S, Meixensberger J, Neumuth T (2013) Intervention time prediction from surgical low-level tasks. J Biomed Inform 46(1):152–161PubMedCrossRefGoogle Scholar

Copyright information

© CARS 2013

Authors and Affiliations

  1. 1.Universität Leipzig, Innovation Center Computer Assisted SurgeryLeipzigGermany

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