Sequential drug decision problems in long-term medical conditions: a case Study of Primary Hypertension Eunju Kim ba, ma, msc

1.4Motivations and research objectives

This study was motivated by the clinical reality that drug switching commonly happens in long-term medical conditions, but there is limited evidence and research about the optimal treatment pathway. Clinical guidelines in the treatment of primary hypertension are an example, with recommended treatment algorithms being based on piece-wise evidence, resulting in lack of clear consensus and differences between guidelines^{[8-10, 63]}. Furthermore those recommended clinical guidelines have not been tested in clinical trials or in economic evaluations.

From a methodological perspective, conventional economic evaluations have been interested in evaluating the cost-effectiveness of a drug at a specific point in the disease pathway: however, the most cost-effective drugs can be different as the patient’s health state changes over time. Although there were some studies, which considered the treatment sequences in a broader disease pathway, there has been no economic evaluation to address the global optimality of SDDPs in a long-term health condition.

Due to the practical importance of stochastic sequential decision problem, many approximate optimisation methods have been developed. None of those optimisation algorithms works consistently better than others. The performance can be different depending on the type of optimisation problems: therefore, this study aims to set down the definitions of SDDPs mathematically to understand the nature of SDDPs, to examine the potential methods to identify optimal or near-optimal sequential treatment strategies in the context of a multiple drugs, multiple switches and multiple health states decision space problem; and to discuss the performance of the proposed methods using a case study of primary hypertension.

The objectives of this study are:

1. 
   To develop the formal definitions of SDDPs using the framework of MDP.
   
2. 
   To review approximate optimisation methods to identify the set of methods appropriate for SDDPs.
   
3. 
   To develop a de novo hypertension cost-effectiveness model considering blood pressure lowering effects of sequential use of antihypertensive drugs.
   
4. 
   To test the feasibility and performance of selected approximate optimisation methods using the developed hypertension model.