Abstract

To describe our methods to compare patient-reported symptoms of acute myeloid leukemia and the corresponding documentation by healthcare providers in the electronic health record. Patients with acute myeloid leukemia experience many distressing symptoms, particularly related to chemotherapy. The timely recognition and provision of evidence-based interventions to manage these symptoms can improve outcomes. However, lack of standardized formatting for symptom documentation within electronic health records leads to challenges for clinicians when accessing and comprehending patients' symptom information, as it primarily exists in narrative forms in various parts of the electronic health record. This variability raises concerns about over- or under-reporting of symptoms. Consistency between patient-reported symptoms and clinician's symptom documentation is important for patient-centered symptom management, but little is known about the degree of agreement between patient reports and their documentation. This is a detailed description of the study's methodology, procedures and design to determine how patient-reported symptoms are similar or different from symptoms documented in electronic health records by clinicians. Exploratory, descriptive study. Forty symptoms will be assessed as patient-reported outcomes using the modified version of the Memorial Symptom Assessment Scale. The research team will annotate symptoms from the electronic health record (clinical notes and flowsheets) corresponding to the 40 symptoms. The degree of agreement between patient reports and electronic health record documentation will be analyzed using positive and negative agreement, kappa statistics and McNemar's test. We present innovative methods to comprehensively compare the symptoms reported by acute myeloid leukemia patients with all available electronic health record documentation, including clinical notes and flowsheets, providing insights into symptom reporting in clinical practice. Findings from this study will provide foundational understanding and compelling evidence, suggesting the need for more thorough efforts to assess patients' symptoms. Methods presented in this paper are applicable to other symptom-intensive diseases.

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