Return to homepagePandemic Pact

Improving Methods for Extracting Data from Clinicians' Notes in Electronic Health Records

  • Funded by Patient-Centered Outcomes Research Institute
  • Total publications:0 publications

Grant number: unknown

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Key facts

  • Disease

    COVID-19

  • Start & end year

    N/A

  • Known Financial Commitments (USD)

    $346,641

  • Funder

    Patient-Centered Outcomes Research Institute

  • Principal Investigator

    PhD. Stephane M Meystre

  • Research Location

    United States of America

  • Lead Research Institution

    Medical University of South Carolina

  • Research Priority Alignment

    N/A

  • Research Category

    Health Systems Research

  • Research Subcategory

    Health information systems

  • Special Interest Tags

    Data Management and Data Sharing

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

With this enhancement, the research team will create new methods to study COVID-19 that use natural language processing, or NLP. With NLP, computer programs interpret written language from clinical notes and make it easier to sort, study, and extract COVID-19 related information. The team will look at clinicians' notes found in patient electronic health records. They will capture information about COVID-19, including: Exposure to the novel coronavirus Symptoms and diseases Laboratory tests Medicines and treatments Other health problems patients may have