International Journal of Computer Assisted Radiology and Surgery

, Volume 6, Issue 1, pp 59–71

Analysis of surgical intervention populations using generic surgical process models

Authors

    • Innovation Center Computer Assisted Surgery (ICCAS)Universität Leipzig
  • Pierre Jannin
    • Faculty of MedicineINSERM, U746
    • VisAGeS Unit/ProjectINRIA
    • CNRS, UMR 6074, IRISAUniversity of Rennes I
  • Juliane Schlomberg
    • Department of OphthalmologyUniversity Hospital Leipzig
  • Jürgen Meixensberger
    • Innovation Center Computer Assisted Surgery (ICCAS)Universität Leipzig
    • Department of NeurosurgeryUniveristy Hospital Leipzig
  • Peter Wiedemann
    • Department of OphthalmologyUniversity Hospital Leipzig
  • Oliver Burgert
    • Innovation Center Computer Assisted Surgery (ICCAS)Universität Leipzig
Original Article

DOI: 10.1007/s11548-010-0475-y

Cite this article as:
Neumuth, T., Jannin, P., Schlomberg, J. et al. Int J CARS (2011) 6: 59. doi:10.1007/s11548-010-0475-y

Abstract

Purpose

According to differences in patient characteristics, surgical performance, or used surgical technological resources, surgical interventions have high variability. No methods for the generation and comparison of statistical ‘mean’ surgical procedures are available. The convenience of these models is to provide increased evidence for clinical, technical, and administrative decision-making.

Methods

Based on several measurements of patient individual surgical treatments, we present a method of how to calculate a statistical ‘mean’ intervention model, called generic Surgical Process Model (gSPM), from a number of interventions. In a proof-of-concept study, we show how statistical ‘mean’ procedure courses can be computed and how differences between several of these models can be quantified. Patient individual surgical treatments of 102 cataract interventions from eye surgery were allocated to an ambulatory or inpatient sample, and the gSPMs for each of the samples were computed. Both treatment strategies are exemplary compared for the interventional phase Capsulorhexis.

Results

Statistical differences between the gSPMs of ambulatory and inpatient procedures of performance times for surgical activities and activity sequences were identified. Furthermore, the work flow that corresponds to the general recommended clinical treatment was recovered out of the individual Surgical Process Models.

Conclusion

The computation of gSPMs is a new approach in medical engineering and medical informatics. It supports increased evidence, e.g. for the application of alternative surgical strategies, investments for surgical technology, optimization protocols, or surgical education. Furthermore, this may be applicable in more technical research fields, as well, such as the development of surgical workflow management systems for the operating room of the future.

Keywords

Surgical workflow Surgical Process Model Health care evaluation mechanisms Cataract surgery

Copyright information

© CARS 2010