title: DisTeam: A decision support tool for surgical team selection.
abstract: Surgical service providers play a crucial role in the healthcare system. Amongst all the influencing factors, surgical team selection might affect the patients' outcome significantly. The performance of a surgical team not only can depend on the individual members, but it can also depend on the synergy among team members, and could possibly influence patient outcome such as surgical complications. In this paper, we propose a tool for facilitating decision making in surgical team selection based on considering history of the surgical team, as well as the specific characteristics of each patient.
  
  
  
  DisTeam (a decision support tool for surgical team selection) is a metaheuristic framework for objective evaluation of surgical teams and finding the optimal team for a given patient, in terms of number of complications. It identifies a ranked list of surgical teams personalized for each patient, based on prior performance of the surgical teams. DisTeam takes into account the surgical complications associated with teams and their members, their teamwork history, as well as patient's specific characteristics such as age, body mass index (BMI) and Charlson comorbidity index score.
  
  
  
  We tested DisTeam using intra-operative data from 6065 unique orthopedic surgery cases. Our results suggest high effectiveness of the proposed system in a health-care setting. The proposed framework converges quickly to the optimal solution and provides two sets of answers: a) The best surgical team over all the generations, and b) The best population which consists of different teams that can be used as an alternative solution. This increases the flexibility of the system as a complementary decision support tool.
  
  
  
  DisTeam is a decision support tool for assisting in surgical team selection. It can facilitate the job of scheduling personnel in the hospital which involves an overwhelming number of factors pertaining to patients, individual team members, and team dynamics and can be used to compose patient-personalized surgical teams with minimum (potential) surgical complications.
authors.affiliation: Department of Biomedical Engineering, University of Florida, 1064 Center Dr., Gainesville, FL 32611, USA. Electronic address: ashkan.ebadi@ufl.edu.
authors.forename: Ashkan
authors.initials: A
authors.lastname: Ebadi
authors.affiliation: Department of Anesthesiology, University of Florida, 1600 SW Archer Rd., Gainesville, FL 32603, USA.
authors.forename: Patrick J
authors.initials: PJ
authors.lastname: Tighe
authors.affiliation: Department of Anesthesiology, University of Florida, 1600 SW Archer Rd., Gainesville, FL 32603, USA.
authors.forename: Lei
authors.initials: L
authors.lastname: Zhang
authors.affiliation: Department of Biomedical Engineering, University of Florida, 1064 Center Dr., Gainesville, FL 32611, USA.
authors.forename: Parisa
authors.initials: P
authors.lastname: Rashidi
mesh_terms: D003657:Decision Making; D020000:Decision Support Systems, Clinical; D013502:General Surgery / Q000592:standards; D006801:Humans; D019637:Orthopedic Procedures; D010348:Patient Care Team; D000078329:Workforce
keywords: Decision support; Genetic algorithm; Intra-operative; Orthopedics; Patients’ outcome; Surgical team selection