Implementation of this educational program showed the feasibility of a continent-wide interprofessional massive course on hospital acquired-infections in Latin America, in the two main languages spoken in the region. Next steps included a new edition of this course and a "New Challenges" course on hospital-acquired infections, which were successfully implemented in the second semester of 2015 by the same institutions.

This article was migrated. The article was marked as recommended. The COVID-19 pandemic has profoundly impacted the medical meetings planned for 2020. This health crisis has caused the cancellation, postponement or a pivot in educational design to virtual formats. In the latter case, the format for virtual meetings has remained very similar to the cancelled face-to-face meeting, by using primarily web conferencing systems.This article intends to start a dialogue with the medical education and events community about possible delivery formats. Among them, the concept of an "Extended Congress" is introduced.The extended congress uses the extension of time, space and languages to a scientific meeting. It aims to: 1) unleash the reach of traditional meetings through the use of technology to access larger audiences in different languages, across a country and internationally, with local leaders to help interpret the knowledge and localize it, and 2) to improve knowledge translation into practice through a sequential and active learning process.An ongoing example is described as a proof of concept: the Latin American Peritoneal Dialysis Extended Congress attracted 774 remote participants from over 20 countries, 93% of whom were paid registrants. Initially designed as a hybrid (live plus remote) event scheduled for March 2020, it had to be reframed as a remote only meeting due to the COVID-19 pandemic, thus protecting the health of members while providing continued value to the organization and attendees of the event.With this experience in mind, the authors are currently designing programs in the United States, through collaboration with the University of Virginia Office of Continuing Medical Education.In summary, the design of meetings can better utilize and integrate technology and reach larger audiences with a blend of formats. Those organizations that adapt more quickly to offer these events will concentrate more of the share, as seen with the adoption of technology by other industries.

Massive open online courses (MOOCs) bring about the opportunity to reach large international audiences of health professionals. However, change in clinical practice eventually needs social interaction, to validate the new knowledge with trusted peers, in the agreement and adoption phases of change. How can meaningful dialogue take place without scaling up expert tutoring? The extensive experience from social network applications such as Facebook or Twitter provides an opportunity to improve dialogue among peers and with experts automatically and seamlessly, as part of what is called social learning analytics (SLA). Large amounts of data about prior relationships among participants in a course-similar to Facebook and other social applications-, among participants and course materials-similar to Netflix or Amazon-, as well as natural language processing, could be obtained, and then analyzed and used to improve the educational processes and outcomes. In this paper, a series of examples with pilot uses of SLA in the context of massive online courses for physicians and other health care professionals are described. They include: 1) Forecasting of academic accomplishment. 2) Teambased face-to-face learning as part of massive online courses. 3) Analysis of existing connections, to ensure the most connected discussion groups of course participants. 4) Facebook-like dialogue with other course participants who are previously related, as well as with the Course Faculty. 5) Crowdsourcing and friendsourcing, for recommending useful study materials or future courses. 6) Natural language processing, to classify posts in online discussions. The intent of this manuscript is to create awareness in the medical education community that this type of analysis is possible and potentially useful, to receive feedback on the possible functionalities as well as critique these developments, and to create a space for collaboration in research and innovation projects with other interested

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In reply to the reviewers' comments, the following changes were made: -References were added and the text was completed in relation to these references, particularly about communities of practice and the revolution of interaction triggered by the new information and communication technologies. -The results were summarized and the discussion was extended. -A clarification was made regarding social media in CME and the scope of the article. -A reference published in MedEdPublish about the same topic after the first version was added AbstractMassive open online courses (MOOCs) bring about the opportunity to reach large international audiences of health professionals. However, change in clinical practice eventually needs social interaction, to validate the new knowledge with trusted peers, in the agreement and adoption phases of change. How can meaningful dialogue take place without scaling up expert tutoring?The extensive experience from social network applications such as Facebook or Twitter provides an opportunity to improve dialogue among peers and with experts automatically and seamlessly, as part of what is called social learning analytics (SLA). Large amounts of data about prior relationships among participants in a course -similar to Facebook and other social applications-, among participants and course materials -similar to Netflix or Amazon -, as well as natural language processing, could be obtained, and then analyzed and used to improve the educational processes and outcomes.In this paper, a series of examples with pilot uses of SLA in the context of massive online courses for physicians and other health care professionals are described. They include: 1) Forecasting of academic accomplishment. 2) Teambased face-to-face learning as part of massive online courses. 3) Analysis of existing connections, to ensure the most connected discussion groups of course participants. 4) Facebook-like dialogue with other course participants who are previously related, as well as with the Course Faculty. 5) Crowdsourcing and friendsourcing, for recommending useful study materials or future courses. 6) Natural language processing, to classify posts in online discussions. It should be noted that the article does not address the use of Facebook or Twitter in continuing medical education (CME), but instead, the use of their approaches in CME.The intent of this manuscript is to create awareness in the medical education community that this type of analysis is possible and potentially useful, to receive feedback on the possible functionalities as well as critique these developments, and to create a space for collaboration in research and innovation projects with other interested parties.