We model this problem as a multi-trip vehicle routing problem with time windows using stochastic programming with recourse to represent the random urgent requests. We develop an insertion based heuristic with a tabu-search improvement phase to solve this problem. Our computational results show that this approach obtains significant improvement in travel costs as well as in route similarity over alternative methods, both on randomly generated data as well as on a real data set provided by a leading healthcare provider in Southern California.