title: Assessing and using the multiple correlated components of the burden of disease in decision-making in health care.
abstract: In medical decision-making, we must (a) establish the patient's prognosis, and (b) identify the therapeutic strategy that will best improve that prognosis. The prognosis is the projected progression over time of the cumulative probability of (a) mortality, (b) morbidity, (c) disability, (d) psychological distress, and (e) resource use. Our modeling employs parametric representations and multivariate analysis to produce the predicted individual and joint probabilities of any range of each measure and of combinations of the measures. The predicted probabilities are consistent with their observed values. We have demonstrated, we believe, the feasibility of analyzing and predicting the burden of disease as a means to support decision-making at the bedside and the policy level.
authors.affiliation: Division of Transplantation, HSB, HRSA, DHHS, 6507 Divine Street, McLean, VA 22101, USA. RCBailey@mac.com
authors.forename: R Clifton
authors.initials: RC
authors.lastname: Bailey
authors.forename: Monica J Y
authors.initials: MJ
authors.lastname: Lin
authors.forename: Henry
authors.initials: H
authors.lastname: Krakauer
mesh_terms: D017281:Cost of Illness; D003695:Delivery of Health Care; D006801:Humans; D015233:Models, Statistical; D015999:Multivariate Analysis; D010818:Practice Patterns, Physicians'; D011379:Prognosis; D014481:United States