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.

抽象的 在如何与患者建立良好关系和治疗患者方面存在偏见，这取决于患者的种族、民族、 性别、社会经济地位、LGBTQ+ 地位、残疾、成瘾和其他因素。 无意识的偏见（我们的信仰、态度和价值观影响我们如何看待世界的方式 以及其中的人）广泛存在并影响患者的健康结果，我们的团队开发了 Counter。 偏差训练模拟 (CBTsim)，一种创新且独特的培训计划，利用模拟来 减少隐性偏见对人们互动和做出影响他人的决策的影响。 专为警务和军事专业人员开发，以提高他们与不同群体互动的能力 CBTsim 与医疗保健密切相关，而医疗保健领域存在偏见。 培训通常以视频或讲座为基础，可能无法有效减少偏见的影响 患者与临床医生的关系 (PCR) 和随后的医疗保健服务是本研究的目的。 开发“CBTsim Healthcare”并评估其在减少护士对待护士的偏见方面的有效性 拟议的研究将在华盛顿州立大学护理学院联合进行。 首先，我们将开发 CBTsim Healthcare。 然后，我们将根据对医疗保健差异文献的广泛回顾来制定情景。 对 100 名护士进行的随机对照试验，以测试护士将接受的 CBTsim Healthcare 的有效性。 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）将观看一段 1 小时的视频，内容涉及当前典型的医疗保健隐性偏见 然后，所有 100 名护士将接受 2 小时的干预后测试。 内隐关联测试（IAT）测量隐性偏见，问卷调查测量偏见，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差的护理场景 最后，我们将在产后 6 个月内对治疗组和对照组护士进行住院跟踪。 评估医疗保健差异的干预措施，使用患者对护理量表的满意度进行衡量 （定量测量）和记录 PCR 经验的叙述（定性测量） 所有专业。 卫生机构已确定减少医疗保健中的隐性偏见以及由此产生的少数族裔健康 健康差异的经济影响是一个极其重要和紧迫的问题。 每年估计 2,300 亿美元，对社会正义的影响是不可估量的。 由于我们现有的关系（例如，在 AHRQ R01 HS025965-01 上），但我们预计 CBTsim 医疗保健可以针对其他医疗保健专业团体进行修改，并且可以产生革命性的结果 对减少全国医疗保健服务中的偏见的影响。