ComprehENotes: Assessing patients' comprehension of their medical conditions and treatment
Hong Yu
Many medical patients are now able to directly access their electronic health records (EHR). Providing such direct access has been shown to lead to improved healthcare outcomes through the patient’s enhanced understanding of their medical conditions and treatment. However, EHR contain medical jargon that challenge populations with lower health literacy. Low health literacy is associated with several negative health outcomes, including failure to follow up on doctor’s orders and repeat health problems. ComprehENotes is the first ever tool that helps clinicians assess the health literacy of their patients with regard to EHR, identifying areas of weakness that they need to work to improve with their patients. The tool is test comprising a series of multiple choice questions that assess patients’ understanding across six major health conditions: cancer, COPD, diabetes, heart failure, hypertension, and liver failure. The questions were administered to hundreds of respondents, and natural language processing was used to evaluate and verify the effectiveness of the questions in gauging patient comprehension.
• First tool to evaluate patient’s understanding of their electronic health records • Simple to administer to patients: can be completed during a visit or online • Can be used for targeted interventions to improve patient’s understanding • Improve patient care and outcomes
• Clinical tool doctors can administer to patients • Tool for the medical research community • Methodology can be applied to other medical conditions
Hong Yu, Ph.D., is Professor and Principal Investigator UMMS BioNLP Group, Dept. of Quantitative Health Sciences, University of Massachusetts Medical School Worcester; Adjunct Professor, School of Computer Science, University of Massachusetts Amherst; Research Health Scientist, VA Central Western Massachusetts. She is an elected fellow of the American College of Medical Informatics. She received her Ph.D. from the Department of Biomedical Informatics at Columbia University. Her research focuses on information retrieval and natural language processing and their applications to the biomedical and healthcare domain. AskHERMES is one of the few online systems that provide answers to biomedical questions. NoteAid is a system that translates electronic medical record (EMR) notes to lay language comprehensible to patients. She also mines data from EMRs for healthcare outcome studies.
Available for Licensing and/or Sponsored Research
UMA 18-065
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