In the last decade, eSupport (Internet-reliant therapy) has gained substantial attention, both in research and practice. Several studies in psychology show that structured eSupport (e.g. Computerized Cognitive Behavioural Therapy), is promising both with regard to therapeutic efficacy and cost-effectiveness. However, the transition from face-to-face therapy to eSupport creates new challenges for therapists, such as lack of (traditional) structure and access to secondary information (e.g. body language) about their patients. In this paper, a design science research approach has been employed in the context of eSupport. Drawing on the knowledge base of face-to-face conversations, face-to-face therapy, and pragmatic IS theory, a framework for patient indicators has been designed. The design has been justified through both (i) descriptive evaluations based on the selected knowledge base, and (ii) experiences collected in a stakeholder-centric design process, including experimental evaluation of an eSupport platform that implement the indicator framework. The framework was designed to allow new indicators to be ?plugged in? dynamically and inserted into tailorable lists. New indicators can be created either through specialization of an indicator base class, or by configuring metadata for generic indicators that tap into an action log. Indicator values are cached, both to boost performance and to support trend analysis of patient indicators. We conclude that the indicator framework serves to improve support for therapists: It offers structure and access to both primary and secondary information in new ways. In doing so, it meets some of the key challenges that therapists encounter in the transition to eSupport.