Analysis of surgical intervention populations using generic surgical process models
- 375 Downloads
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.
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.
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.
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.
KeywordsSurgical workflow Surgical Process Model Health care evaluation mechanisms Cataract surgery
Unable to display preview. Download preview PDF.
- 6.Münchenberg JE, Brief J, Raczkowsky J, Wörn H, Hassfeld S, Mühling J (2001) Operation planning of robot supported surgical Interventions. In: Proceedings of IEEE/RSJ international conference on intelligent robots and systems. IEEE Computer Society, pp 547–552Google Scholar
- 12.MacKenzie CL, Ibbotson A, Cao CGL, Lomax A (2001) Hierarchical decomposition of laparoscopic surgery: a human factors approach to investigating the operating room environment 10(3):121–128Google Scholar
- 13.Meng F, D’Avolio LW, Chen AA, Taira RK, Kangarloo H (2005) Generating models of surgical procedures using UMLS concepts and multiple sequence alignment. AMIA Annu Symp Proc 520–524Google Scholar
- 16.Cook JE, Wolf AL (1995) Automating process discovery through event-data analysis. In: ICSE’95: Proceedings of the 17th international conference on software engineering, New York, pp 73–82Google Scholar
- 17.Agrawal R, Gunopulos D, Leymann F (1998) Mining process models from workflow logs. In: Ramos I, Alonso G, Schek H, Saltor F (eds) Advances in database technology—EDBT’98, pp 469–483Google Scholar
- 18.Schimm G (2004) Mining exact models of concurrent workflows 53(3):265-281Google Scholar
- 19.de Medeiros AKA, Weijters AJMM, van der Aalst WMP (2005) Genetic process mining: a basic approach and its challenges. In: Workshop on Business Process Intelligence (BPI), NancyGoogle Scholar
- 20.Aalst WMP, Dongena BFV, Herbst J, Marustera L, Schimm G, Weijters AJMM (2003) Workflow mining: a survey of issues and approaches 47(2):237–267Google Scholar
- 21.AWMF (2008) Leitlinien für Diagnostik und Therapie. (German clinical guidelines) [Internet]. Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften e. V. Available from: http://www.awmf-leitlinien.de/
- 22.AHRQ (2008) Agency for Health Care Research and Quality: National Guideline Clearinghouse [Internet]. Available from: http://www.guideline.gov
- 23.Neumuth T, Durstewitz N, Fischer M, Strauss G, Dietz A, Meixensberger J et al (2006) Structured recording of intraoperative surgical workflows. In: Horii SC, Ratib OM (eds) SPIE medical imaging 2006—PACS and imaging informatics: progress in biomedical optics and imaging. Bellingham, WA CID 61450AGoogle Scholar
- 24.Cleary K, Kinsella A, Mun SK (2005) OR2020 Workshop report: operating room of the future. In: Lemke HU, Inamura K, Doi K, Vannier MW, Farman AG (eds) Proceedings of the 19th Computer Assisted Radiology and Surgery CARS, pp 832–838Google Scholar