Abstract: In adverse drug event (ADE) monitoring and reporting, drug-related messages (60) are detected in one or more social media message streams as messages that include a name of a monitored drug. ADE reports (62) are extracted from the drug-related messages using an ADE classifier (46). The extracted ADE reports are validated by comparison with known ADEs of the monitored drug stored in an ADE knowledge base (64). Extracted ADE reports that fail the validating are collected in a non-validated ADE reports database (72). A report (74) is generated including information on at least one previously unrecognized ADE for which extracted ADE reports in the non-validated ADE reports database satisfy a previously unrecognized ADE criterion (in terms of number of messages or number of unique patients reporting the ADE).

Abstract: Various embodiments described herein relate to methods and apparatuses for documenting data by tracking user interactions with an interface. Users such as medical personnel or the like rely on clinical documentation to treat a patient. By automatically generating clinical documentation based on user interactions with an interface when reviewing patient data, users are not required to spend time in generating clinical documentation themselves.