A Modeling Framework for Decision Support in Periprosthetic Joint Infection Treatment

Abstract

In this paper, we present a framework, which aims at facilitating the choice of the best strategy related to the treatment of periprosthetic joint infection (PJI). The framework includes two models: a detailed non-Markovian model based on the decision tree approach, and a general Markov model, which captures the most essential states of a patient under treatment. The application of the framework is demonstrated on the dataset provided by Russian Scientific Research Institute of Traumatology and Orthopedics “R.R. Vreden”, which contains records of patients with PJI occurred after total hip arthroplasty. The methods of cost-effectiveness analysis of treatment strategies and forecasting of individual treatment outcomes depending on the selected strategy are discussed.

A Decision Support Framework for Periprosthetic Joint Infection Treatment: A Cost-Effectiveness Analysis Using Two Modeling Approaches

“…To address this issues, we developed a Markov model with generalized states as an alternative approach. The detailed description of the model is provided in [ 31 ], the major highlights of it are given below.…”

“…At the same time, the time is not tracked in this model type, which makes it complicated to compare time-dependent costs. As it was described in [ 31 ], the framework supports the assignments of parameters, related to the impact of the intervention, to each branch of the tree. To assess the cost-effectiveness of the treatment methods, we measured intervention costs in rubles and measured utility of the patient calculated in QALY units.…”