Counter Bias Training Simulation (CBTsim) Healthcare: A Novel Approach for Reducing the Impact of Implicit Bias on Healthcare Delivery

反偏见培训模拟 (CBTsim) 医疗保健：减少隐性偏见对医疗保健服务影响的新方法

• 批准号: 10637978
• 负责人: Lois James
• 金额: $ 44.62万
• 依托单位: WASHINGTON STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-22 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10637978
• 关键词: Address; Affect; African American population; Analgesics; Attitude; Awareness; Belief; Care given by nurses; Centers for Disease Control and Prevention (U.S.); Cessation of life; Client satisfaction; Communication; Complex; Conscious; Control Groups; Decision Making; Development; Discipline of Nursing; Disparity; Effectiveness; Ethnic Origin; Gender; Health; Health Professional; Healthcare; Homelessness; Hospitals; Hour; Human; Implicit Association Test; Inequality; Inequity; Intervention; Learning; Lesbian Gay Bisexual Transgender Queer; Manikins; Measures; Medical center; Methods; Military Personnel; Nurses; Outcome; Patient Care; Patients; Performance; Persons; Pharmaceutical Preparations; Police; Police officer; Prejudice; Public Health; Questionnaires; Race; Randomized, Controlled Trials; Recommendation; Research; Review Literature; Social Justice; Socioeconomic Status; Testing; Therapeutic; Training; Training Programs; Unconscious State; United States Agency for Healthcare Research and Quality; United States National Institutes of Health; Universities; Washington; addiction; care outcomes; college; design; disability; economic impact; effectiveness testing; experience; explicit bias; healing; health care delivery; health care disparity; health disparity; implicit bias; innovation; lectures; medication administration; member; minority health disparity; minority healthcare; novel; novel strategies; post intervention; programs; racial bias; simulation; skills; social group; treatment group; unconscious bias; virtual experiments

ABSTRACT Bias in how clinicians form relationships with and treat patients exists based on patient race, ethnicity, gender, socio-economic status, LGBTQ+ status, disability, addiction and other factors. Implicit or unconscious biases (the ways in which our beliefs, attitudes, and values influence how we see the world and the people in it) are widespread and affect patients’ health outcomes. Our team has developed Counter Bias Training Simulation (CBTsim), an innovative and unique training program that uses simulation to reduce the impact of implicit bias on how people interact and make decisions that affect others. Versions have been developed for policing and military professionals to enhance their ability to interact with diverse groups of citizens in unbiased ways. CBTsim has great relevance to healthcare, for which existing bias trainings are typically video or lecture based, and may be ineffective at reducing the impact of bias on patient-clinician relationships (PCR) and consequent healthcare delivery. The purpose of this study is to develop “CBTsim Healthcare” and evaluate its effectiveness at reducing bias in how nurses treat their patients. The proposed study will be jointly conducted in the Washington State University College of Nursing Simulation Lab and Providence Medical Center in Spokane. First, we will develop CBTsim Healthcare scenarios based on an extensive review of the literature on healthcare disparities. Then, we will conduct a randomized control trial with 100 nurses to test the effectiveness of CBTsim Healthcare. Nurses will receive 2 hours of baseline testing, then 50 (treatment group) will receive a 4-hour CBTsim Healthcare training and the other 50 (control group) will watch a 1-hour video on implicit bias in healthcare, typical of current standard practice. Then, all 100 nurses will receive 2 hours of post-intervention testing. Testing will include the implicit association test (IAT) to measure implicit bias, questionnaires to measure prejudice, and patient care scenarios using simulation mannequins to test for bias in PCR and other aspects of healthcare delivery. Finally, we will track treatment and control group nurses in the hospital for 6 months following the intervention to assess disparities in healthcare, measured using patient satisfaction with nursing care scales (quantitative measure) and narratives to document experience of PCR (qualitative measure). All major health agencies have identified reduction of implicit bias in healthcare and resulting minority health disparities as a matter of extreme importance and urgency. The economic impact of health disparities is an estimated $230 billion a year, and the social justice impact is immeasurable. Our current focus on nurses is due to our existing relationship (e.g., on AHRQ R01 HS025965-01), however we anticipate that CBTsim Healthcare could be modified for other healthcare professional groups and could have a revolutionary impact on reducing bias in healthcare delivery nationwide.

摘要 临床医生如何与患者建立关系和治疗患者的偏见存在于患者的种族，民族， 性别、社会经济地位、LGBTQ+地位、残疾、成瘾和其他因素。隐式或 无意识偏见（我们的信仰、态度和价值观影响我们看待世界的方式） 和其中的人）分布广泛并影响患者的健康结果。我们的团队开发了Counter 偏差培训模拟（CBTsim），一个创新和独特的培训计划，使用模拟， 减少内隐偏见对人们如何互动和做出影响他人的决定的影响。版本 已制定警务和军事专业人员，以提高他们的能力， 以公正的方式对待公民群体。CBTsim与医疗保健有很大的相关性， 培训通常是基于视频或讲座的，可能无法有效减少偏见对 患者-临床医生关系（PCR）和随之而来的医疗保健服务。本研究的目的是 开发“CBTsim医疗保健”，并评估其在减少护士如何对待他们的偏见方面的有效性。 患者拟议的研究将在华盛顿州立大学护理学院联合进行 模拟实验室和斯波坎的普罗维登斯医疗中心。首先，我们将发展CBTsim医疗保健 方案的基础上广泛审查的文献保健差距。然后，我们将进行一次 随机对照试验，100名护士测试CBTsim医疗保健的有效性。护士将收到 2小时的基线测试，然后50名（治疗组）将接受4小时的CBTsim Healthcare培训， 另外50人（对照组）将观看一个1小时的视频，内容是医疗保健中的隐性偏见， 标准做法。然后，所有100名护士将接受2小时的干预后测试。测试将包括 测量内隐偏见的内隐联想测试（IAT），测量偏见的问卷，以及患者 使用模拟人体模型测试PCR和医疗保健其他方面的偏倚的护理场景 交付.最后，我们将跟踪治疗组和对照组护士在医院6个月后， 干预措施，以评估医疗保健的差异，使用患者对护理量表的满意度进行测量 （定量测量）和叙述以记录PCR经验（定性测量）。所有主要 卫生机构已经确定减少医疗保健中的隐性偏见， 这是一个极端重要和紧迫的问题。健康差距的经济影响是一个 据估计，每年约有2300亿美元，对社会正义的影响是不可估量的。我们目前对护士的关注点是 由于我们现有的关系（例如，关于AHRQ R 01 HS 025965 -01），但我们预计CBTsim 医疗保健可以修改为其他医疗保健专业团体，并可能有革命性的 减少全国医疗服务偏差的影响。