Putting the Patient in Patient Reported Outcomes : A Robust Methodology for Health Outcomes Assessment

This paper proposes a novel two-stage approach to modeling health-related quality-of-life (HRQoL) outcomes. The approach allows a patient-centered interpretation by estimating regression coe fficients based on the multi-dimensional HRQoL profi le, but maintains the parsimony of the quality-adjusted life-year (QALY) framework by re-interpreting incremental eff ects in the QALY domain. Through a series of Monte Carlo simulations, the proposed methodology is shown to be more robust to the distributional properties of QALYs, thereby avoiding the potential bias introduced when converting the multi-dimensional HRQoL into a one-dimensional QALY. The approach also allows researchers to more easily update cost- and comparative-eff ectiveness results as new HRQoL scoring algorithms develop for new patient populations. I provide an application to the estimation of incremental eff ects of demographic and clinical variables on HRQoL following surgical treatment for adult scoliosis and spinal deformity patients