The evolution of the Internet has provided new and more efficient communication and collaboration channels between individuals, empowering them to share health information and to interact more and more using social media channels. Information quality is frequently identified as one of the main limitations of social media in healthcare. The objective of the paper is to discuss the social implications and limitations on information quality in healthcare social media, and particularly to contribute to the analysis and development of healthcare social networks (SN) and online healthcare social network services (SNS). For that reason, a formal architectural analysis of healthcare SN and SNS has been proposed, considering the complexity of both systems, but stressing on quality of Information aspects. Any social system - and its network of interrelations - can be analyzed as a real world system. Therefore, it is possible to model the structural components, interrelations and functionality (system architecture) of healthcare SN and SNS. The Generic Component Model (GCM) has demonstrated to be an ideal architectural framework for any real system’s analysis. Based on the GCM, the architecture of quality aware healthcare SNS is proposed. Information quality is addressed in the domain dimension of the GCM, supported by the definition of information quality policies. The practical implementation of quality-driven online SNS and information quality policies was demonstrated by the development of an online SNS supporting health promotion programs in a healthcare institution. In order to evaluate the relevance of the information quality policies proposed, a descriptive study was performed, in which the content published in the online SNS was selected strictly following the information quality policy. The study demonstrated that users’ perceived information quality was high. The paper addresses sociotechnical aspects of social media by providing a formal method for the management of information quality in online healthcare social networks