Building a normative decision support system for clinical and operational risk management in hemodialysis.
This paper describes the design and implementation of a decision support system for risk management in hemodialysis (HD) departments. The proposed system exploits a domain ontology to formalize the problem as a Bayesian network. It also relies on a software tool, able to automatically collect HD data, to learn the network conditional probabilities. By merging prior knowledge and the available data, the system allows to estimate risk profiles both for patients and HD departments. The risk management process is completed by an influence diagram that enables scenario analysis to choose the optimal decisions that mitigate a patient's risk. The methods and design of the decision support tool are described in detail, and the derived decision model is presented. Examples and case studies are also shown. The tool is one of the few examples of normative system explicitly conceived to manage operational and clinical risks in health care environments.
Cornalba
Chiara
C
Department of Applied Statistics and Economics ("L. Lenti"), University of Pavia, 27100 Pavia, Italy. chiara.cornalba@gmail.com
Bellazzi
Roberto G
RG
Bellazzi
Riccardo
R
D000465:Algorithms; D020000:Decision Support Systems, Clinical; D006801:Humans; D012016:Reference Values; D006435:Renal Dialysis / Q000706:statistics & numerical data*; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012984:Software