25 Models and Causal Thinking CAUSATION One of the great challenges underlying intervention research is to deter- mine what constitutes proof of causation. The goal of outcomes research is to isolate the effect of treatment on the patient and/or disease being treated. The underlying challenge is to demonstrate that the relationship is causal. Distinguishing cause from association is one of the great chal- lenges of science, especially clinical science. Much of health services research and outcomes research draws on epi- demiology, which is primarily directed at identifying factors associated with illness and identifying its cause. Here we are interested in the causes of improvement that result from defined interventions. Hence, some of the principles work well, but some need extrapolations. Principles of causation have been around for quite a while, but ironi- cally, they have changed as scientific measurement has improved and science has become more efficient and complex. One of the early phi- losophers who addressed causation was David Hume (Beauchamp, 1999). He laid out a series of postulates, or criteria, for a causal relationship. For example, to say that A causes B, the following must be true: 1. A must be consistently associated with B. 2. A must always precede B. 3. There must be a theoretical connection of A to B. CHAPTER 2 © Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION.
