Final answer:
Dr. Gordis must know the Negative Predictive Value to determine the probability that a patient truly does not have disease Z after testing negative, as it reflects the accuracy of the test in ruling out disease in those who receive a negative result.
Step-by-step explanation:
To accurately determine the probability that a patient truly does not have disease Z after testing negative, Dr. Gordis must know the Negative Predictive Value (NPV) of the test. Negative Predictive Value is the proportion of people who test negative and are actually disease-free. It factors in the specificity of the test (the probability that the test correctly identifies those without the disease) and the prevalence of the disease in the population (the overall rate at which the disease occurs).
Although not directly asked for, it's worth noting that sensitivity (the probability that the test correctly identifies those with the disease) and specificity are intrinsic properties of the test, while Positive Predictive Value (PPV) and NPV are affected by the prevalence of the disease in the population being tested.