Decision Analysis and Markov Modeling in Urology

Purpose

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.

Materials and 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.

Key Words: urology, decision support techniques, Markov chains

Abbreviations and Acronyms: ANN, artificial neural networks, DA, decision analysis, EV, expected value, MM, Markov model, OP, open prostatectomy, QALY, quality-adjusted life years, QOL, quality of life, RAP, robotic assisted prostatectomy