New patient-centered models of quality-of-life measures for evaluation of interventions for multi-stage diseases

This paper focuses on the development of quantitative dynamic models for measuring the total quality of life of patients with multi-stage diseases using disutility functions. The physician and the patient can jointly use these models to evaluate different medical interventions and make a decision on choosing the appropriate intervention for the patient. The non-homogeneous continuous-time Markov process model is first generalized for the process of the disease (e.g., change of stages in a cancer). The probability that a patient is in a particular stage at some point in time, and the expected time that the patient stays in that stage, are formulated using this stochastic model. A disutility function which is commonly used in economics is incorporated into the stochastic model to allow measurement of the patient's total experience with his/her illness and medical treatments as a function of time.