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 coefficients based on the multi-dimensional HRQoL profile, but maintains the parsimony of the quality-adjusted life-year (QALY) framework by re-interpreting incremental effects 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-effectiveness results as new HRQoL scoring algorithms develop for new patient populations. I provide an application to the estimation of incremental effects of demographic and clinical variables on HRQoL following surgical treatment for adult scoliosis and spinal deformity patients.