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Summary: This review reports on the workshop “Reassembling Health: exploring the role of the Internet of Things.” The aim of the workshop was to bring together professionals from different disciplines in order to envision future scenarios enabling patient participation, home-, mobile-, and self-care. In particular, this report offers a discussion of some of the assumptions of the current medical model, and how their renegotiation might make possible the exploration of new participatory health care practices.
Keywords: Design, self-care, patient participation, patient empowerment, chronic-disease, internet of things
Citation: Storni C. Report on the “reassembling health workshop: exploring the role of the internet of things”. J Participat Med. 2010 Sep 27; 2:e10.
Published: September 28, 2010.
Competing Interests: The author has declared that no competing interests exist.

This workshop was part of the event “Are You Ready for the Internet of Things?” which was held at the Center for Digital Cultures and Technology in Brussels on December 4, 2009. It was organized by Council, a new European think tank that studies the Internet of Things and its future ( This conference report is particularly relevant to policy makers, designers and developers of information and communication technology, which supports participatory medicine. The goal of the workshop was to gather professionals from different backgrounds (medicine, social science, computer science and design research) in order to explore the future of the evolving health care landscape, with an eye on the potential key role to be played by the Internet of Things.

The Internet of Things (IoT) refers to new types of wireless, networked technologies that go beyond the traditional desktop screen and are instead embedded in various objects and tools. Through a wide variety of increasingly cheap sensors (implanted, wearable, mobile, environmental, and so on) the IoT opens up a variety of new socio-technical scenarios. A large number and variety of objects and environments can be augmented with computational and communication capabilities. For example, it becomes possible to “ask” your umbrella for weather forecasts (, or let your plants tweet you when they are “thirsty” ( In the health care domain, examples include having pill bottles that glow or text to remind you to take your next pill (, clothes that monitor your vital signs, or mobile phones that allow you to perform tests and manage your treatment, act in emergency situations, and stay in touch with your caregivers.

In the workshop’s introduction, a summary of current changes occurring in Western health care systems was presented. With an aging population and an increase in prevalence of chronic diseases, the rising demand for new treatments predicts a possible shortage of human resources as well as increasing costs. In order to minimize hospitalizations, efficiently allocate specialized personnel, and reduce costs, the notions of patient empowerment and mobile-, home-, and self-care generate understandable enthusiasm, and are becoming phenomena of increasing importance. The potential for moving care away from hospitals and clinics corresponds to a never-before-seen movement of medical information and technology from traditional settings and expert uses to domestic environments and lay uses. This migration is not trivial — especially in the context of chronic disease — and is central to creating the conditions that will help to drive participatory medicine.

The workshop sessions addressed the assumptions and weaknesses of the dominant medical model, how they are often reflected in design of medical technology and how we might rethink some of them to allow more robust patient participation. In particular, a shift toward a chronic disease model was presented and used to question the mere application of a biomedical perspective (positivist, reductionist, and based on compliance) in the design of tool to support lay people in managing their chronic disease (Fig. 1). The assumption is that the traditional model falls short in addressing the emerging need of the new one.

Fig 1. Characters of the traditional model and of the emerging one enabled by the IoT.

The potential of crowd-sourcing the gathering, production and interpretation of health data to a scalable mass of patients—enabled by the IoT—was discussed. This idea of patients being technologically enabled to produce health data has recently emerged (eg, the work of Hardey,[1] Akrich,[2] Callon,[3] Dyson,[4] Frydman,[5] Rabeharisoa and Callon,[6] and [7] These developments challenge the traditional paradigm of knowledge creation and validation in medicine and enable patients to manage and coordinate their care — and, more importantly, to gather new data, explore what matters from their own perspective, and possibly discover new things as well as to safely experiment and tinker with their treatments. As Utley-Smith et al. also noted, “Quasi-experimental trials and qualitative mixed-methods studies […] have been used with increasing sophistication in supplementing or supplanting designs that leave too many questions of the interactions between causality and context unanswered.[8]” The IoT can be of great support to this emerging and hybrid way of producing new medical knowledge by extending the traditional medical model to make it a more participatory one, that is better aligned to a chronic disease world.

The meeting participants noted that the problem implied by the diffusion of harmful and unsubstantiated knowledge and information is real in a world where a mass of lay patients starts to produce data and freely share their experiences. Knowledge produced in this way is not peer reviewed, and its conditions of production can only be mapped with difficulty. However, making and keeping it publicly accessible and open might suggest that a “Wikipedia/eBay model” could work in the production of new hybrid medical knowledge. Affected people, many of whom can be expected to contribute, might be even more motivated than many experts to look, read, try, report, comment on, and criticize available medical knowledge, information, and practices. Experiences such as those of Patients Like Me users show how this is already happening. In an open system, malicious knowledge tends to gradually be muted out. We do not know if this way of validating knowledge is worse or better than the traditional one. We know that it is quicker, involves a remarkably higher number of participants, and it might be less constrained by traditional assumptions and secluded procedures. However, the central point is that in order for this model to work, data should be aggregated, made public, and made freely accessible, in addition to being anonymous.

The second topic that was discussed was: Who is supposed to own the data? Today, patient-produced data often belongs to the corporation that sells the tools and the infrastructure to support them. Data and their format still tend to be proprietary: Patients can access it, but are often not allowed to export it in order to re-appropriate and possibly compare it with other data. Participants agreed that a new culture of sharing should be encouraged to ensure the production and exploration of new medical possibilities in which active patients play a key role. Similarly, participants agreed with the idea that keeping data-mining algorithms “open source” would ensure more visibility and stimulate the generation of new hypotheses. In addition, as we learn from open source movements and the logic of Copyleft licenses, keeping algorithms open would also allow for a continuous public redesign that can bring about the refinement of research agendas and the exploration of new options (eg, regarding the co-occurrence of environmental factors and certain symptoms, or the effects of certain drugs in chronic treatment). Then traditional medical trials can intervene at a later stage to validate what emerges from patient-generated and openly mined data.

It is a long shot and a revolutionary one, but technological innovation can make it a possibility worth exploring. As Suchman observes, “Technological change can […] be an occasion for either the expansion of existing forms of authoritative knowledge, or for their transformation… At the core of this project is the question not only of how information flows, but of who defines what constitutes ‘information’ in the first place.[9]” With this in mind, we hope that designers and policy makers dealing with new, emerging technologies and exploring the possibilities of the IoT in the medical setting will not take the traditional epidemiological paradigm for granted, and will be brave enough to acknowledge the need for an integration of multiple perspectives where no voice should be marginalized. As Stange wrote, in participatory medicine we need: “not discipline-specific language, but new words that describe resonant ideas that have emerged from paying attention — from working, experiencing, and making sense across usual boundaries.[10]


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The author wishes to acknowledge funding support from the Irish HEA PRTLI Cycle 4 FutureComm ( program.

Copyright: © 2010 Cristiano Storni. Published here under license by The Journal of Participatory Medicine. Copyright for this article is retained by the author, with first publication rights granted to the Journal of Participatory Medicine. All journal content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License. By virtue of their appearance in this open-access journal, articles are free to use, with proper attribution, in educational and other non-commercial settings.