John E. Goulionis

Medical decision making for patients with Parkinson disease under Average Cost Criterion

Parkinsons disease (PD) is one of the most common disabling neurological disorders and results in substantial burden for patients, their families and the as a whole society in terms of increased health resource use and poor quality of life. For all stages of PD, medication therapy is the preferred medical treatment. The failure of medical regimes to prevent disease progression and to prevent long-term side effects has led to a resurgence of interest in surgical procedures. Partially observable Markov decision models (POMDPs) are a powerful and appropriate technique for decision making. In this paper we applied the model of POMDPs as a supportive tool to clinical decisions for the treatment of patients with Parkinsons disease. The aim of the model was to determine the critical threshold level to perform the surgery in order to minimize the total lifetime costs over a patients lifetime (where the costs incorporate duration of life, quality of life, and monetary units). Under some reasonable conditions reflecting the practical meaning of the deterioration and based on the various diagnostic observations we find an optimal average cost policy for patients with PD with three deterioration levels.

Structural properties for a two-state partially observable Markov decision process with an average cost criterion

Abstract This paper investigates an optimal replacement problem for a discrete-time Markovian deterioration system. We consider partially observable Markov decision processes with finite core state and observation spaces and finite action set. The problem is to obtain an optimal replacement control-limit policy. Sufficient conditions, are then derived for a bounded solution to the average cost optimality equation to exist. Furthermore, under some reasonable conditions reflecting the practical meaning of the deterioration, structural properties for average costs policies are obtained for a two state replacement problem, and we develop a solution procedure utilizing these structural properties. We have that control permits working directly making it suitable for dealing with real-world processes and applications.

On the decision rules of cost-effective treatment for patients with diabetic foot syndrome

Objective: To assess the cost-effectiveness of two treatments (medical treatment and amputation) in patients with diabetic foot syndrome, one of the most disabling diabetic complications. Diabetes mellitus is a massive health care problem worldwide with a current prevalence of 150 millions diabetic cases, estimated to increase to 300 million cases in 2025. Methods: Integrating medical knowledge and advances into the clinical setting is often difficult due to the complexity of the algorithms and protocols. Clinical decision support systems assist the clinician in applying new information to patient care through the analysis of patient-specific clinical variables. We require strategic decision support to analyze the cost-effectiveness of these programs compared to the status quo. We provide a simple partially observable Markov model to investigate that issue, and we propose an heuristic algorithm to find the best policy of intervention. Results: This study assesses the potential cost-effectiveness of two alternative treatment interventions in patients with diabetic foot syndrome. The implementation of the heuristic algorithm solution will assist doctors in clinical decision making, and health care organizations in evaluating medication choices for effective treatment. Finally, our study reveals that treatment programs are highly cost-effective for patients at high risk of diabetic foot ulcers and lower extremity amputations.

The partially observable Markov decision processes in healthcare: an application to patients with ischemic heart disease (IHD)

Partially observable Markov Decision Process POMDP have been suggested a most popular tool to express sequential decision making under uncertainty. The generality of the standard POMDP model, however, limits practical application of the framework due to the computational complexity of associated solution methods. To alleviate this obstacle we have proposed a specialized POMDP form and our goal is to determine an optimal or nearly optimal policy for the treatment of patients with IHD. This well constructed POMDP model has practical advantage over clinical studies (no risk for the life of patients and low cost), though the latter are necessary to perform before making significant changes to treatment guidelines.

PARTIALLY OBSERVABLE MARKOV DECISION PROCESSES AND PERIODIC POLICIES WITH APPLICATIONS

This paper treats the infinite horizon discounted cost control problem for partially observable Markov decision processes. Sondik studied the class of finitely transient policies and showed that their value functions over an infinite time horizon are piecewise linear (p.w.l) and can be computed exactly by solving a system of linear equations. However, the condition for finite transience is stronger than is needed to ensure p.w.l. value functions. In this paper, we introduce alternatively the class of periodic policies whose value functions turn out to be also p.w.l. Moreover, we examine a more general condition than finite transience and periodicity that ensures p.w.l. value functions. We implement these ideas in a replacement problem under Markovian deterioration, investigate for periodic policies and give numerical examples.

Stationary policies with Markov partition property

Abstract This paper treats the infinite horizon discounted cost control problem for partially observable Markov decision processes (POMDPs). Sondik [14] studied the class of finitely transient policies and showed that their value functions over an infinite time horizon are piecewise linear (p.w.l) and can be computed exactly by solving a system of linear equations. However the condition for finite transience is stronger than is needed to ensure p.w.l value functions. In this paper we introduce alternatively the class of periodic policies whose value functions turn out to be also p.w.l. Moreover we examine a more general condition than finite transience and periodicity. We implement these ideas in a replacement problem under Markovian deterioration, investigate for periodic policies and give numerical examples.

A validation of two temporal disease clusters tests with a simple epidemic model

Abstract Modern medicine has made great advances in the cure of numerous diseases, but still its more remarkable results lie in the field of prevention. The early detection of an epidemic’s outbreak is of an outmost importance in order to avoid the epidemic’s spread. Since we do not possess a single detection method that would perfectly apply to all cases it is fundamental to know in advance how precise our opted method’s results will be. In this paper a validation of two temporal disease clusters tests with the simple epidemic model is presented. Additionally, the behavior of both methods is analyzed when risk factors are added in.