Interactive crowdsourcing to spontaneous reporting of Adverse Drug Reactions

Abstract

Adverse Drug Reactions (ADRs) has become a worldwide problem that draws the attention of people from all racial and ethnic groups. The number of deaths caused by ADRs has greatly increased and led to many drug withdrawals in the last decades. Recent research findings indicate that most ADRs can be effectively prevented to some extent by using computeraided information technologies. Though many spontaneous reporting systems (SRSs) have been built to enhance the pharmacovigilance, the ADRs data is still very sparse because the large amount of reports obtained from consumers contains insufficient hints to identify a possible causal relationship between an adverse event and drug. Based on this motivation, we developed AdverseTracking, a spontaneous reporting system of ADRs via crowdsourcing. Our proposed system interacts with consumers through a Q&A interface and collects the ADR reports. The decision tree support vector machine (DTSVM) based on the genetic algorithm is used in our system to automate the Q&A procedure. We carried out experiments to evaluate the performance at Peking University First Hospital. As demonstrated by the results, our system is an efficient tool to track and discover adverse events in the consumers' reports of ADRs, which facilitates the detection of "signal".

Developing a Crowdsourcing Approach and Tool for Pharmacovigilance Education Material Delivery

“…The use of crowdsourcing has been discussed in pharmacovigilance, but this has been in the context of collecting adverse event reports and for subsequent signal detection. An example is reported by Chen et al [12]. We have developed a tool and, through a small focussed proof-ofconcept study, shown its usability in terms of data link upload and subsequent search function.…”

A Survey on Security, Privacy, and Trust in Mobile Crowdsourcing

“…Many MCS applications have been developed and are used for environment monitoring [2,4], infrastructure monitoring [3,10,11], qualityof-experience analysis [8,9], surface perception [5], and public safety [7]. In parallel to MCS applications, there are some studies aiming at improving the energy-efficiency in MCS [32,33].…”