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Validating a Framework for Coding Patient-Reported Health Information to the Medical Dictionary for Regulatory Activities Terminology: An Evaluative Study.

Sonja BrajovicDavid A BlaserMeaghan BradleyChristine CaligtanSally OkunMarni HallCarol A Pamer
Published in: JMIR medical informatics (2018)
PatientsLikeMe MedDRA coding of PGHD was generally comparable to how the FDA would code similar data, applying the MTS:PTC principles. Discordant coding resulted from several reasons but mostly reflected a difference in purpose. The MTS:PTC coding principles aim to capture the most specific reported information about an ADE, whereas PatientsLikeMe may code patient-reported symptoms and ADEs to more general MedDRA terms to support patient engagement among a larger group of patients. This study demonstrates that most verbatim reports of symptoms and ADEs collected by a PGHD source, such as the PatientsLikeMe platform, could be reliably coded to MedDRA terminology by applying the MTS:PTC guide. Regarding all secondary use of novel data, understanding coding and standardization principles applied to these data types are important.
Keyphrases
  • patient reported
  • health information
  • electronic health record
  • social media
  • end stage renal disease
  • big data
  • healthcare
  • chronic kidney disease
  • newly diagnosed
  • machine learning