Pharmacovigilance for a revolving world: prospects of patient-generated data on the internet.

Abstract

The past 10 years have seen the advent of smartphones and a massive increase in the use and influence of the internet and social media in our daily lives. The means by which we interact with one another and with the world’s information have fundamentally changed. Navigation is one example: when I drive from Uppsala to Stockholm, not only does my phone now direct me where to go, but its instructions adapt in real-time based on the current flow of traffic, as crowdsourced from the phones of fellow drivers. In health, we have seen the emerging movement of the quantified self where individuals track exercise and sleep patterns, along with information on diet, and aspects of their physical and mental state, with the intent of understanding what promotes their own good health and well-being (a daunting causal inference task!). So, too, have we seen the growth of internet communities where patients store and interact with their own health data, and share experiences, with the ultimate aim of learning from one another for better health outcomes. We have yet to see the full impact of these developments in pharmacovigilance, but movement has begun. The important role of patients in identifying, describing, and ultimately avoiding, harm from medicines is increasingly recognized [1, 2], and modern technologies are being explored to facilitate patient engagement [3]. Information on direct patient reports in pharmacovigilance differs in certain respects from information provided by health professionals, but has been found to be of complementary value [4]. Interestingly, in one study, direct patient reports in Denmark and Norway (collected electronically) were found to be better documented, on average, than reports from health professionals [5]. Mobile applications for spontaneous reporting are being piloted, and we have seen initiatives to use social media sites to stimulate submission of individual case reports [6]. This may add to our understanding of adverse drug reactions and provide opportunities to directly engage with and support patients [7], but also comes with challenges such as how to effectively protect sensitive information, account for selection biases, and minimise the risk of intended misuse [7, 8]. In parallel, patient-generated data on the internet is beginning to be explored as a primary basis for analysis of possible adverse drug reactions. In a paper recently published in Drug Safety, Freifeld et al. [9] described an analysis of Twitter microblog posts for references to drugs and adverse events, with comparison to reporting patterns in the US FDA Adverse Event Reporting System (FAERS). Other researchers have explored online discussion fora and internet search patterns for similar purposes [10–12]. Together, these studies begin to accumulate evidence for the technical feasibility of identifying references to possible adverse drug reactions in patient-generated data on the internet, and of analysing these patterns to characterise and understand patients’ experiences and concerns. Such G. N. Noren (&) Uppsala Monitoring Centre, WHO Collaborating Centre for International Drug Monitoring, Box 1051, 751 40 Uppsala, Sweden e-mail: niklas.noren@who-umc.org