  We consider the first exit time of a nonnegative Harris-recurrent Markov
process from the interval $[0,A]$ as $A\to\infty$. We provide an alternative
method of proof of asymptotic exponentiality of the first exit time (suitably
standardized) that does not rely on embedding in a regeneration process. We
show that under certain conditions the moment generating function of a suitably
standardized version of the first exit time converges to that of $\Exp(1)$, and
we connect between the standardizing constant and the quasi-stationary
distribution (assuming it exists). The results are applied to the evaluation of
a distribution of run length to false alarm in change-point detection problems.
