A new method for measuring the informational value of a clinical information system is proposed. The method is based on the information theoretic principle which defines information to be equivalent to the removal of uncertainty from a system. According to this principal, a clinical information system would have value so far as it removes uncertainty in the physician's ability to predict clinical outcomes. It is therefore proposed here to quantify information transfer by measuring a physician's predictive accuracy by asking him/her to estimate the probabilities of certain future events and from these estimates assigning him/her a "predictive accuracy score". It is proposed to demonstrate the new tool to measure information transfer by using a randomized single blind study to evaluate a computerized ambulatory medical record system relative to the traditional medical record. We will address four methodological questions concerning the predictive accuracy method: (1) How to choose outcome events to predict which simultaneously are relevant to the important clinical informational issues, are sufficiently broad and do not systematically exclude important aspects of the patients' status, and are free from potential researcher or physician bias. (2) The question of the method's sensitivity to detect clinically important information differences will be addressed by applying the method to situations where a real informational difference is either known or strongly suspected, and the question of external validity by comparing the new tool to the traditional methods for evaluating clinical information systems. (3) The practicality of the method in terms of implementation in actual clinical settings, physician and patient acceptance, and the numbers of patients and physicians required to achieve adequate sample size will be addressed by direct demonstration. (4) The various alternative candidate mathematical functional forms for the predictive accuracy score will be explored and tested by theoretical (mathematical and statistical) techniques as well as by direct comparison on the demonstration data.