The analysis of longitudinal data with informative observation processes has recently attracted a great deal of attention and some methods have been developed.However, most of those methods treat the observation process as a recurrent event process, which assumes that one observation can immediately follow another.For the problem, we present a joint analysis approach for regression analysis of both longitudinal and observation processes and a simulation study is conducted that assesses the finite sample performance of the approach. The asymptotic properties of the proposed estimates are also given and the method is applied to the medical cost data that motivated this study.