Because the majority of health care services are consumed in the last six months of life, mortality prediction can be an important feature of health care budgeting and planning. This study compares the ability of two diagnosis-based risk adjustment systems and health self-report to predict short- and long-term mortality. Data were obtained from the Department of Veterans Affairs (VA) administrative databases. The focus of this article is on the 35,337 patients who voluntarily completed and returned a Short Form Health Survey for veterans (SF-36V).
The researchers found that the predictive ability of the eight-scale (SF-36V) model was less than the diagnosis based variables for 1-year mortality but equal to the Diagnostic Cost Groups (DCG) model for 2–5-year mortality. They noted that survey-based measures may pick up the more permanent/chronic aspects of a patient's health, whereas diagnosis-based measures contain more accurate information on more acute and/or transitory aspects of health. The results suggest that for 1-year planning, diagnosis-based information may be more appropriate. For 5-year planning, a medical facility may want to consider obtaining SF-36V information on potential users by a mass mailing.