@article{mason_denton_shah_smith_2014, title={Optimizing the simultaneous management of blood pressure and cholesterol for type 2 diabetes patients}, volume={233}, ISSN={["1872-6860"]}, DOI={10.1016/j.ejor.2013.09.018}, abstractNote={We present a Markov decision process (MDP) model to determine the optimal timing of blood pressure and cholesterol medications. We study the use of our model for a high-risk population of patients with type 2 diabetes; however, the model and methods we present are applicable to the general population. We compare the optimal policies based on our MDP to published guidelines for initiation of blood pressure and cholesterol medications over the course of a patient’s lifetime. We also present a bicriteria analysis that illustrates the trade off between quality-adjusted life years and costs of treatment.}, number={3}, journal={EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}, author={Mason, J. E. and Denton, B. T. and Shah, N. D. and Smith, S. A.}, year={2014}, month={Mar}, pages={727–738} }
 @article{mason_denton_2012, title={A comparison of decision-maker perspectives for optimal cholesterol treatment}, volume={56}, ISSN={["2151-8556"]}, DOI={10.1147/jrd.2012.2201849}, abstractNote={Medical decisions often involve tradeoff among competing criteria. For example, patients with third-party health insurance are primarily concerned about maximizing their quality-adjusted lifespan, since the majority of the cost burden typically falls on the third-party payer. On the other hand, third-party payers are incented to minimize total healthcare-related costs. Therefore, third-party payers must weigh the short-term cost of treatment against the long-term benefits of avoiding more costly health outcomes associated with disease progression and adverse events. The goal of the societal perspective is to achieve a reasonable balance among these competing criteria of quality-adjusted lifespan and costs. Treatment of diabetes provides a good example of the need to apply multicriteria decision-making models to treatment decisions. Chronic diseases such as diabetes are associated with high medical costs and a large number of available treatment options. In this paper, we use a Markov decision process (MDP) to show how decision-maker perspectives can influence medical treatment decisions related to cardiovascular risk management in patients with type 2 diabetes. We compare optimal treatment decisions from three different perspectives: societal, patient, and third-party payer. We further formulate an inverse MDP model to estimate the implied monetary value of a year of life, from the societal perspective, according to current U.S. treatment guidelines.}, number={5}, journal={IBM JOURNAL OF RESEARCH AND DEVELOPMENT}, author={Mason, J. E. and Denton, B. T.}, year={2012} }
 @article{mason_england_denton_smith_kurt_shah_2012, title={Optimizing Statin Treatment Decisions for Diabetes Patients in the Presence of Uncertain Future Adherence}, volume={32}, ISSN={["1552-681X"]}, DOI={10.1177/0272989x11404076}, abstractNote={Background. Statins are an important part of the treatment plan for patients with type 2 diabetes. However, patients who are prescribed statins often take less than the prescribed amount or stop taking the drug altogether. This suboptimal adherence may decrease the benefit of statin initiation. Objective. To estimate the influence of adherence on the optimal timing of statin initiation for patients with type 2 diabetes. Method. The authors use a Markov decision process (MDP) model to optimize the treatment decision for patients with type 2 diabetes. Their model incorporates a Markov model linking adherence to treatment effectiveness and long-term health outcomes. They determine the optimal time of statin initiation that minimizes expected costs and maximizes expected quality-adjusted life years (QALYs). Results. In the long run, approximately 25% of patients remain highly adherent to statins. Based on the MDP model, generic statins lower costs in men and result in a small increase in costs in women relative to no treatment. Patients are able to noticeably increase their expected QALYs by 0.5 to 2 years depending on the level of adherence. Conclusions. Adherence-improving interventions can increase expected QALYs by as much as 1.5 years. Given suboptimal adherence to statins, it is optimal to delay the start time for statins; however, changing the start time alone does not lead to significant changes in costs or QALYs.}, number={1}, journal={MEDICAL DECISION MAKING}, author={Mason, Jennifer E. and England, Darin A. and Denton, Brian T. and Smith, Steven A. and Kurt, Murat and Shah, Nilay D.}, year={2012}, pages={154–166} }