Yes! The methods of choice for exponentials of large sparse matrices are Krylov methods, and they compute directly $\exp(A)b$ for a given vector $b$ rather than the full matrix $\exp(A)$. Just take $b$ as a vector of the canonical basis, and you're set.

These algorithms are based on approximating the exponential as a rational function (sum of partial fractions), and then solving several shifted linear systems of the form $(A-\tau_k I)x_k=b_k$; hence they should work particularly well for a tridiagonal matrix, for which solves are cheap.

See for instance a chapter in the review  https://doi.org/10.1017/S0962492910000036,  https://doi.org/10.1137/100788860, or http://onlinelibrary.wiley.com/doi/10.1002/gamm.201310002/full, as well as the [Matlab code in Stefan Güttel's webpage](http://guettel.com/) which you can use to compute it.

All these algorithms are approximate (but in the end, what is *not* approximate on a computer?), so you may encounter trouble if the element that you wish to compute is many orders of magnitudes smaller than $\|\exp(A)\|$. In that case, you may be interested in a bound on the decay rate of off-diagonal entries in https://arxiv.org/abs/1501.07376.