Despite the increasing use of telemedicine around the world, little has been done to incorporate quality assurance (QA) into these operations. The purpose of the present study was to examine the feasibility of QA in store-and-forward teleconsulting using a previously published framework. During a 2-year study period, we examined the feasibility of using QA tools in two mature telemedicine networks [Médecins Sans Frontières (MSF) and New Zealand Teledermatology (NZT)]. The tools included performance reporting to assess trends, automated follow-up of patients to obtain outcomes data, automated surveying of referrers to obtain user feedback, and retrospective assessment of randomly selected cases to assess quality. In addition, the senior case coordinators in each network were responsible for identifying potential adverse events from email reports received from users. During the study period, there were 149 responses to the patient follow-up questions relating to the 1241 MSF cases (i.e., 12% of cases), and there were 271 responses to the follow-up questions relating to the 639 NZT cases (i.e., 42% of cases). The collection of user feedback reports was combined with the collection of patient follow-up data, thus producing the same response rates. The outcomes data suggested that the telemedicine advice proved useful for the referring doctor in the majority of cases and was likely to benefit the patient. The user feedback was overwhelmingly positive, over 90% of referrers in the two networks finding the advice received to be of educational benefit. The feedback also suggested that the teleconsultation had provided cost savings in about 20% of cases, either to the patient/family, or to the hospital/clinic treating the patient. Various problems were detected by regular monitoring, and certain adverse events were identified from email reports by the users. A single aberrant quality reading was detected by using a process control chart. The present study demonstrates that a QA program is feasible in store-and-forward telemedicine, and shows that it was useful in two different networks, because certain problems were detected (and then solved) that would not have been identified until much later. It seems likely that QA could be used much more widely in telemedicine generally to benefit patient care.