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Assessing the Readability of Electronic Health Records

Assessing the Readability of Electronic Health Records. Lan VoBa SI 561 Natural Language Processing. Overview of EHRs. What is an EHR? How are they being used? What are the benefits? What are the challenges?. Motivation. How “patient-friendly” are doctors’ notes, letters, etc.?

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Assessing the Readability of Electronic Health Records

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  1. Assessing the Readability of Electronic Health Records Lan VoBa SI 561 Natural Language Processing

  2. Overview of EHRs • What is an EHR? • How are they being used? • What are the benefits? • What are the challenges?

  3. Motivation • How “patient-friendly” are doctors’ notes, letters, etc.? • How difficult to read and understand those documents? • Related work • “Applying Multiple Methods to Assess the Readability of a Large Corpus of Medical Documents” (Wu et al) • Readability formulas used to assess other health-related texts • Automated Readability Index • New Dale-Chall Formula

  4. The Data • UMHS • 120 clinic locations and offices • 45,000 inpatient hospital stays • 1.8 million outpatient visits and surgeries • The records • Freetext • Preparation • 4,133 Letters • 18,217 non-letters • Challenges • Limited access • Poor metadata

  5. Automated Readability Index

  6. New Dale-Chall Formula

  7. Method Automated Readability Index Letters Scores Metadata New Dale-Chall Formula Non-Letters

  8. Results

  9. Future Work • Wu et al • More documents • Remove “headers” • Compare scores to human evaluators to confirm assessment

  10. Thank you! Questions? Comments?

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