Malpractice and malcontent: Analyzing medical complaints in twitter

Abstract

In this paper we report preliminary results from a study of Twitter to identify patient safety reports, which offer a immediate, untainted, and expansive patient perspective unlike any other mechanism to date for this topic. We identify patient safety related tweets and characterize them by which medical populations caused errors, who reported these errors, what types of errors occurred, and what emotional states were expressed in response. Our long term goal is to incorporate this patient input into the patient safety process to improve the handling and reduce occurrence of error.