Polsley, Seth C (2017-08). Identifying Outcomes of Care from Medical Records to Improve Doctor-Patient Communication. Master's Thesis. Thesis uri icon

abstract

  • Between appointments, healthcare providers have limited interaction with their patients, but patients have similar patterns of care. Medications have common side effects; injuries have an expected healing time; and so on. By modeling patient interventions with outcomes, healthcare systems can equip providers with better feedback. In this work, we present a pipeline for analyzing medical records according to an ontology directed at allowing closed-loop feedback between medical encounters. Working with medical data from multiple domains, we use a combination of data processing, machine learning, and clinical expertise to extract knowledge from patient records. While our current focus is on technique, the ultimate goal of this research is to inform development of a system using these models to provide knowledge-driven clinical decision-making.
  • Between appointments, healthcare providers have limited interaction with their
    patients, but patients have similar patterns of care. Medications have common side
    effects; injuries have an expected healing time; and so on. By modeling patient
    interventions with outcomes, healthcare systems can equip providers with better
    feedback. In this work, we present a pipeline for analyzing medical records according
    to an ontology directed at allowing closed-loop feedback between medical encounters.
    Working with medical data from multiple domains, we use a combination of data
    processing, machine learning, and clinical expertise to extract knowledge from patient
    records. While our current focus is on technique, the ultimate goal of this research is
    to inform development of a system using these models to provide knowledge-driven
    clinical decision-making.

publication date

  • August 2017