Ruple Catalina, Brodhead John, Rabinovich Lila, Junghaenel Doerte U, Nakamura Tiffany, Wong Jonathan, De-Oliveira Sophia, Brown Joan, Nguyen Phuong, Horn Jenny, Middleton Renee, Brahe Michelle, Wen Cheng, Rao Sujeet, Nguyen Caroline, Shlamovitz Gil, Marino Dara, Osorno Felipe, Siegel Steven
Center for Economic and Social Research, University of Southern California, Los Angeles, USA.
Department of Internal Medicine, University of Southern California, Los Angeles, United States.
BMC Health Serv Res. 2024 Dec 23;24(1):1643. doi: 10.1186/s12913-024-12131-4.
Burnout is among the greatest challenges facing healthcare today. Healthcare providers have been found to experience burnout at significant rates, with COVID-19 exacerbating the challenge. Burnout in the healthcare setting has been associated with decreases in job satisfaction, productivity, professionalism, quality of care, and patient satisfaction, as well as increases in career choice regret, intent to leave, and patient safety incidents. In this context, there is a growing need to reduce provider burnout through targeted interventions, yet little is known about what types of interventions may be most effective. The present study aims to contribute to and extend prior literature by using rigorous randomized controlled trial (RCT) methodology with a parallel group design to examine the effectiveness of different interventions in decreasing mental distress, increasing self-efficacy and attenuating inefficiencies and dissatisfiers in the work environment to achieve sustainable improvement.'
The present study is an ongoing randomized controlled trial (RCT) that examines the effectiveness of three different types of interventions to reduce provider burnout: an intervention targeting emotional wellbeing and resilience, Electronic Health Record (EHR) skills training, and performance improvement training, relative to a no-treatment control group. This study aims to enroll a total of 400 healthcare providers in a large urban hospital system. Outcomes will be assessed at post-treatment and 6-month follow-up. Key outcomes include burnout, emotional health, intent to leave, EHR mastery, and confidence in performance improvement. Changes in outcome measurements from baseline to post-intervention across the intervention and control groups will be conducted using linear mixed-effects models (LMM).
This study is novel in that it compares several interventions addressing both personal as well as system-level drivers of provider burnout that have been theorized to operate among healthcare providers. In addition, post-treatment and longer-term follow-up assessments will provide insight into the maintenance of effects. Another innovation is the inclusion of different types of patient-facing providers in the study population (doctors, nurses, and therapists).
This study was registered at ClinicalTrials.gov (NCT05780892) on March 10th, 2023.
职业倦怠是当今医疗行业面临的最大挑战之一。研究发现，医疗服务提供者职业倦怠的发生率很高，而新冠疫情使这一挑战更加严峻。医疗环境中的职业倦怠与工作满意度、工作效率、职业素养、医疗质量和患者满意度的下降有关，同时也与职业选择遗憾、离职意愿和患者安全事件的增加有关。在这种背景下，通过有针对性的干预措施来减少医疗服务提供者的职业倦怠的需求日益增长，但对于哪种类型的干预措施可能最有效却知之甚少。本研究旨在通过使用严格的随机对照试验（RCT）方法和并行组设计，为现有文献做出贡献并加以扩展，以检验不同干预措施在减轻心理困扰、增强自我效能以及缓解工作环境中的低效和不满因素以实现可持续改善方面的有效性。
本研究是一项正在进行的随机对照试验（RCT），旨在检验三种不同类型的干预措施相对于无治疗对照组在减少医疗服务提供者职业倦怠方面的有效性：一种针对情绪健康和心理韧性的干预措施、电子健康记录（EHR）技能培训以及绩效改进培训。本研究旨在纳入一家大型城市医院系统中的400名医疗服务提供者。将在治疗后和6个月随访时评估结果。关键结果包括职业倦怠、情绪健康、离职意愿/EHR掌握程度以及对绩效改进的信心。将使用线性混合效应模型（LMM）对干预组和对照组从基线到干预后结果测量的变化进行分析。
本研究的新颖之处在于它比较了几种针对医疗服务提供者职业倦怠的个人和系统层面驱动因素的干预措施，这些因素在理论上被认为在医疗服务提供者中起作用。此外，治疗后和长期随访评估将提供有关效果维持情况的见解。另一项创新是在研究人群中纳入了不同类型的面向患者的医疗服务提供者（医生护士和治疗师）。
本研究于2023年3月1日在ClinicalTrials.gov（NCT05780892）上注册。
