A MARKOVIAN DECISION PROCESS MODEL TO EVALUATE THE EFFECT OF TECHNOLOGY ADOPTION FOR DIABETES TREATMENT

摘要

The changes in patient perception of healthcare consumption, advancement of information technology and the search for reducing healthcare delivery costs have necessitated a closer look at existing business models in chronic disease management. The key impediment in chronic disease management is an ability to facilitate and sustain appropriate patient behavior modification. As a result, the notion of skill transference - modularizing healthcare services to an extent that they can now be performed or composed by the patient itself - assumes greater significance in the evolution of disease management business models and healthcare delivery process. The advances in IT and the general acceptance of Internet-based applications and tools are providing unique opportunities to disrupt hospital-centric processes by facilitating patient empowerment through enabling skill transference (diagnostics, for example), increasing patient engagement and physician interactions (more communication modes). These trends can be leveraged further only if the role of information interventions in healthcare delivery is better understood. ICT-enabled technologies have been adopted to assist Diabetes disease management. Previous researchers developed a chronic disease quadrangle that characterized chronic conditions primarily on the extent of behavior modification required and the motivation to comply with prescribed therapies.rnIn this study, the chronic quadrangle is extended to provide an information perspective, focusing on the degree of Diabetes patient information required to be encoded and the specificityrnof information that is provided to the patient. This extension will provide a basis for defining IT interventions for a particular chronic care domain. We intend to investigate the effects of technology adoption for this disease treatment on morbidity and mortality. Markov-type multi-state models are used to solve the problem of the healthcare delivery process level transferring. Furthermore, with multiple technologies being suitable to adopt, this study employs a Markov decision process to evaluate the cost and benefit for a variety of combinations of technologies used in the different treatment period. This study provides a framework to characterize interventions and insights from the decision process model to evaluate the effect of technology adoption for diabetes treatment.