PatientsLikeMe.com: developing medical research from social data

PatientsLikeMe is an organization that is developing a social networking platform with the aim of collecting patients’ self-reported medical data. The organization exploits the resulting data for research purposes. The data and the information transactions researchers engage in with patients are the only research context for PatientsLikeMe staff. How does PatientsLikeMe manage to produce real-world medical evidence from the data voluntarily contributed by dispersed patients? In order to produce information, the organization needs to cater to the needs of a myriad of local contexts while still collecting data in sufficient quantity and richness. In this study, I show how such an enterprise requires a complex and continuous exercise of balancing between the conflicting demands of patient engagement, necessary for collecting data on such a scale, and semantic context, necessary for collecting data that are sufficiently expressive. The study adds new insight to previous research efforts regarding how information stems from data that translate across contexts in variably standardized forms.