Agreement between patient‐reported and clinically documented symptoms of acute myeloid leukemia: Study protocol

Author:

Chae Sena1ORCID,Bae Jaewon1ORCID,Youn Nayung1ORCID,Lopez Karen Dunn1ORCID,Sutamtewagul Grerk2ORCID,Rakel Barbara1ORCID

Affiliation:

1. College of Nursing The University of Iowa Iowa City Iowa USA

2. Internal Medicine‐Hematology, Oncology, and Blood and Marrow Transplantation, Carver College of Medicine University of Iowa Iowa City Iowa USA

Abstract

AbstractAimTo describe our methods to compare patient‐reported symptoms of acute myeloid leukemia and the corresponding documentation by healthcare providers in the electronic health record.BackgroundPatients 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.DesignExploratory, descriptive study.MethodsForty 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.ConclusionWe 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.ImpactFindings 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.

Funder

National Institute of Nursing Research

Publisher

Wiley

Reference27 articles.

1. Information bias in health research: definition, pitfalls, and adjustment methods

2. American Cancer Society. (2021).Cancer facts & figures 2021.

3. Secondary use of EHR: Data quality issues and informatics opportunities;Botsis T.;Summit on Translational Bioinformatics,2010

4. Impact of electronic health record systems on information integrity: Quality and safety implications;Bowman S.;Perspectives in Health Information Management,2013

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3