title: Can simulation improve the traditional method of root cause analysis: a preliminary investigation.
abstract: BACKGROUND
  The Joint Commission on Accreditation of Healthcare Organizations recommendations for conducting root cause analysis (RCA) include identifying "root causes" and "common-cause variation" rather than "proximate causes" and "special-cause variation" to create interventions. Simulation for health care RCA is a novel technique but has not been compared with traditional RCA methods.
  
  
  METHODS
  All of the RCAs of adverse events conducted at Tulane Hospital between September 2010 and September 2011 were reviewed. A case of missed postprocedural, preoperative hemorrhage resulting in death was chosen. Hospital records were analyzed to identify the presumed root causes. A simulation of the event was developed and conducted. Six test subjects (preoperative and postanesthesia care unit nurses) participated in the simulation. Root causes identified by simulation analysis were compared with those identified by traditional RCA.
  
  
  RESULTS
  In 2 of 6 simulations, the adverse event was duplicated. The root cause identified by standard RCA technique was inattention to signs of bleeding in the patient/ lack of appropriate monitoring of the patient by nursing staff ("special-cause variation"). Simulation-based RCA revealed that the root cause was not only inadequate monitoring, but also the lack of physical presence of physicians in the care environment ("common-cause variation"). Simulation-based RCA identified root causes more amenable to intervention.
  
  
  CONCLUSIONS
  This study demonstrates that simulation-based RCA can identify additional root causes amenable to making health care interventions when compared with traditional RCA.
authors.affiliation: Department of Surgery, Tulane School of Medicine, New Orleans, LA 70112, USA.
authors.forename: Eric R
authors.initials: ER
authors.lastname: Simms
authors.forename: Douglas P
authors.initials: DP
authors.lastname: Slakey
authors.forename: Meghan E
authors.initials: ME
authors.lastname: Garstka
authors.forename: Steven A
authors.initials: SA
authors.lastname: Tersigni
authors.forename: James R
authors.initials: JR
authors.lastname: Korndorffer
mesh_terms: D007591:Joint Commission on Accreditation of Healthcare Organizations; D008145:Louisiana; D017146:Models, Organizational; D010043:Outcome and Process Assessment, Health Care / Q000379:methods* / Q000458:organization & administration*; D060891:Root Cause Analysis; D014481:United States