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Hidden in Plain Sight: Stigmatizing Language in Patient Medical Records

隐藏在众目睽睽之下：患者病历中的污名化语言

基本信息

批准号：
10365551
负责人：
MARY CATHERINE BEACH
金额：
$ 69.23万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-01-01 至 2026-11-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10365551
关键词：
Affect Age Algorithms Area Attention Attitude Behavior Bypass Canis familiaris Caring Clinical Computerized Patient Records Consensus Drug Prescriptions Education Elderly Feedback Focus Groups Gender Goals Health Professional Health system Healthcare Healthcare Systems Impairment Individual Judgment Language Measures Medical Medical Records Methods Natural Language Processing Obesity Oral Pathway interactions Patients Pattern Persons Physicians Politics Quality of Care Race Reading Records Role Sickle Cell Anemia Social Class Social status Speech Stereotyping Stigmatization Substance Use Disorder Taxonomy Testing Vision Work Writing base disparity reduction ethnic identity health care quality health literacy implementation science implicit bias improved individual patient medical specialties patient health information pilot test racial and ethnic racial disparity sex substance abuser

项目摘要

ABSTRACT Our healthcare system does not treat patients equally: some receive poorer quality care based on their racial/ ethnic identity, social class, health literacy, age, gender or medical conditions such as obesity, sickle cell disease, and substance use disorders. While there may be many factors that contribute to these disparities, implicit bias among clinicians is one important factor that remains difficult to measure. Clinicians may convey and acquire bias towards patients from each other when communicating orally or when writing/reading medical records. Although medical records are an integral method of communicating about patients, few studies have evaluated patient records as a means of transmitting bias from one clinician to another. Our own preliminary work has found that language used in medical records has a direct influence on subsequent clinicians who read the notes, both in terms of their attitudes towards the patient and their medication prescribing behavior; that there are racial disparities in the use of stigmatizing language; and that this language reflects actual attitudes held by the clinicians. This is an important and overlooked pathway by which bias can be passed from one clinician to another, further impairing healthcare quality for the individual patient as well as exacerbating disparities overall for those who are stigmatized. Our overarching goal is to improve the quality and equity of care for persons who are disrespected and stigmatized in healthcare. The specific aims of this proposal are: (1) to define and develop a taxonomy of stigmatizing language in medical records using qualitative analyses with input from clinicians and patients across 5 different medical specialty areas, (2) to measure and test for bias in the use of stigmatizing language in medical records using natural language processing (NLP) that can efficiently detect and quantify stigmatizing language in electronic patient records, and then (3) to reduce stigmatizing language in medical records using proven implementation science (IS) strategies (stakeholder engagement, education, audit and feedback, and champions) to motivate and enable health system change. Every encounter with a patient is documented in the medical record. Because language may have a powerful role in influencing subsequent clinician attitudes and behavior, attention to the language used in medical records could have a large impact on the promotion of respect and reduction of disparities for stigmatized groups.

抽象的我们的医疗保健系统并没有平等地对待患者：有些人因种族/种族而接受质量较差的护理种族认同、社会阶层、健康素养、年龄、性别或健康状况，如肥胖、镰状细胞病、和物质使用障碍。虽然造成这些差异的因素可能有很多，但隐性偏见临床医生之间的差异是一个仍然难以衡量的重要因素。临床医生可以传达和获取在口头交流或书写/阅读病历时对患者存在偏见。尽管医疗记录是沟通患者的一种不可或缺的方法，但很少有研究评估患者记录作为将偏见从一名临床医生传递给另一名临床医生的一种手段。我们自己的前期工作有发现医疗记录中使用的语言对随后阅读记录的临床医生有直接影响，他们对患者的态度和用药行为；认为有种族使用侮辱性语言的差异；并且这种语言反映了人们所持的实际态度临床医生。这是一个重要但被忽视的途径，通过它可以将偏见从一位临床医生传递给另一位临床医生。另一方面，进一步损害个体患者的医疗质量并加剧整体差异对于那些被污名化的人。我们的首要目标是提高对以下人群的护理质量和公平性：在医疗保健领域受到不尊重和侮辱。本提案的具体目标是： (1) 定义和发展使用临床医生的输入进行定性分析，对医疗记录中的污名化语言进行分类 5 个不同医学专业领域的患者，(2) 测量和测试污名化使用中的偏见使用自然语言处理 (NLP) 来识别医疗记录中的语言，可以有效地检测和量化电子病历中的污名化语言，然后（3）减少医疗中的污名化语言使用经过验证的实施科学 (IS) 策略（利益相关者参与、教育、审计和反馈和倡导者）来激励和实现卫生系统变革。每一次与病人的接触都是记录在医疗记录中。因为语言可能会对后续的影响发挥强大的作用临床医生的态度和行为，对医疗记录中使用的语言的关注可能会对促进对受侮辱群体的尊重并减少差异。