title: Decision analysis and Markov modeling in urology.
abstract: OBJECTIVE
  The process of decision making in medicine has become increasingly complex. This has developed as the result of increasing amounts of data, often without direct information or answers regarding a specific clinical problem. The use of mathematical models has grown and they are commonly used in all areas. We describe and discuss the application of decision analysis and Markov modeling in urology.
  
  
  METHODS
  We define decision analysis and Markov models, providing a background and primer to educate the urologist. In addition, we performed a complete MEDLINE database search for all decision analyses in all disciplines of urology, serving as a reference summarizing the current status of the literature.
  
  
  RESULTS
  The review provides urologists with the ability to critically evaluate studies involving decision analysis and Markov models. We identified 107 publications using decision analysis or Markov modeling in urology. A total of 36 studies used Markov models, whereas the remainder used standard decision analytical models. All areas of urology, including oncology, pediatrics, andrology, endourology, reconstruction, transplantation and erectile dysfunction, were represented.
  
  
  CONCLUSIONS
  Decision analysis and Markov modeling are widely used approaches in the urological literature. Understanding the fundamentals of these tools is critical to the practicing urologist.
authors.affiliation: Department of Urology, Urologic Outcomes Research Group, University of California-San Francisco Comprehensive Cancer Center, University of California-San Francisco, USA. mhsieh@urology.ucsf.edu
authors.forename: Michael H
authors.initials: MH
authors.lastname: Hsieh
authors.forename: Maxwell V
authors.initials: MV
authors.lastname: Meng
mesh_terms: D003661:Decision Support Techniques; D006801:Humans; D008390:Markov Chains; D015233:Models, Statistical; D012680:Sensitivity and Specificity; D014572:Urology / Q000706:statistics & numerical data*